CS 785 Fall 2004 Gheorghe Tecuci tecucigmu edu

CS 785 Fall 2004 Gheorghe Tecuci tecuci@gmu. edu http: //lac. gmu. edu/ Learning Agents Center and Computer Science Department George Mason University 2004, G. Tecuci, Learning Agents Center

Overview Knowledge-based agents Knowledge base: Object ontology + Rules Rule-based problem solving Control of the problem solving process 2004, G. Tecuci, Learning Agents Center

What are intelligent agents An intelligent agent is a system that: • perceives its environment (which may be the physical world, a user via a graphical user interface, a collection of other agents, the Internet, or other complex environment); • reasons to interpret perceptions, draw inferences, solve problems, and determine actions; and • acts upon that environment to realize a set of goals or tasks for which it was designed. input/ sensors user/ environment 2004, G. Tecuci, Learning Agents Center output/ effectors Intelligent Agent

The architecture of an intelligent agent Implements a general problem solving method that uses the knowledge from the knowledge base to interpret the input and provide an appropriate output. Intelligent Agent Input/ Sensors User/ Environment Problem Solving Engine Learning Engine Output/ Effectors Knowledge Base Ontology Implements learning methods for extending and refining the knowledge in the knowledge base. Rules/Cases/… Data structures that represent the objects from the application domain, general laws governing them, actions that can be performed with them, etc. 2004, G. Tecuci, Learning Agents Center

Problem Solving Approach: Task Reduction A complex problem solving task is performed by: • successively reducing it to simpler tasks; • finding the solutions of the simplest tasks; • successively composing these solutions until the solution to the initial task is obtained. Knowledge Base Object Ontology Reduction Rules Composition Rules 2004, G. Tecuci, Learning Agents Center

Overview Knowledge-based agents Knowledge base: Object ontology + Rules Rule-based problem solving Control of the problem solving process 2004, G. Tecuci, Learning Agents Center

The structure of the knowledge base Knowledge Base = Object ontology + Task reduction rules The object ontology is a hierarchical description of the objects from the domain, specifying their properties and relationships. It includes both descriptions of types of objects (called concepts) and descriptions of specific objects (called instances). The task reduction rules specify generic problem solving steps of reducing complex tasks to simpler tasks. They are described using the objects from the ontology. 2004, G. Tecuci, Learning Agents Center

The structure of the knowledge base (cont. ) Knowledge Base = Object ontology + Task reduction rules A task reduction rule is an IF-THEN structure that expresses the condition C under which a task T 1 can be reduced to the simpler tasks T 1 a, or to a set of simpler tasks T 11, … , T 1 n. 2004, G. Tecuci, Learning Agents Center T 1 C T 1 a T 1 C T 11 T 12 … T 1 n

Fragment of the object ontology governing_body ad_hoc_ governing_body established_ governing_body other_type_of_ governing_body state_government feudal_god_ king_government other_state_ government democratic_ government monarchy group_governing_body other_ group_ governing_ body dictator deity_figure representative_ parliamentary_ democracy government_ of_Italy_1943 totalitarian_ government police_ state government_ of_US_1943 government_ of_Britain_1943 military_ dictatorship religious_ dictatorship fascist_ state communist_ dictatorship 2004, G. Tecuci, Learning Agents Center government_ of_USSR_1943 government_ of_Germany_1943 democratic_ council_ or_board autocratic_ leader theocratic_ government religious_ dictatorship theocratic_ democracy chief_and_ tribal_council

The instances and the concepts are organized into generalization hierarchies like this hierarchy of governing bodies. Notice, however, that the generalization hierarchies are not always as strict as this one, where each concept is a subconcept of only one concept. For instance, the concept “strategic_raw_material” is both a subconcept of “raw_material” and a subconcept of “strategically_essential_resource_or_infrastructure_element”. 2004, G. Tecuci, Learning Agents Center

Fragment of feature ontology has_as_controlling_leader D: agent R: person has_as_religious_leader D: governing_body R: person has_as_god_king D: governing_body R: person has_as_monarch D: governing_body R: person has_as_military_leader D: governing_body R: person has_as_political_leader D: governing_body R: person has_as_head_of_government D: governing_body R: person 2004, G. Tecuci, Learning Agents Center has_as_commander_in_chief D: force R: person has_as_head_of_state D: governing_body R: person

An object feature is itself defined as a subconcept of another object feature, as illustrated in the previous slide. Therefore, the object features are also hierarchically organized. Notice that if feature 1 is a subconcept of feature 2, than the domain of feature 1 should be less general than or at most as general as the domain of feature 2. The same condition should hold between the ranges of the two features. For instance, “has_as_political_leader” is a subconcept of “has_as_controling_leader”. The domain of the first feature is “governing_body” which is less general than the domain of the second feature, which is “agent. ” Also, the range of “has_as_political_leader” is the same as the range of “has_as_controling_leader”. 2004, G. Tecuci, Learning Agents Center

Object expressions One can define more complex concepts as logical expressions involving the basic concepts from the object ontology. In the following expression, for instance, ? O 1 represents a force that has as industrial factor an industrial capacity that generates essential war materiel from the strategic perspective of a multi-member force that includes ? O 1 ? O 2 ? O 3 is force has_as_industrial_factor ? O 2 is industrial_capacity generates_essential_war_materiel_from_ the_strategic_perspective_of is multi_member_force has_as_member ? O 1 2004, G. Tecuci, Learning Agents Center ? O 3

Ontology matching allows one to answer complex questions about the knowledge represented in the ontology, as illustrated in the following: Question: Is there any force ? O 1 that has as industrial factor an industrial capacity that generates essential war materiel from the strategic perspective of a multi-member force that includes ? O 1? Answer: Yes, US_1943 is a force that has as industrial factor industrial_capacity_of_US_1943 that generates essential war materiel from the strategic perspective of the Allied_Forces_1943 which is a multi-member force that includes US_1943. 2004, G. Tecuci, Learning Agents Center

Ontology matching: example Question Object ontology Answer force ? O 1 US_1943 ? O 2 industrial_capacity_ of_US_1943 force instance-of ? O 3 Allied_forces_1943 subconcept-of single_member_force subconcept-of single_state_force ? O 1 industrial_capacity has_as_industrial_factor multi_state_force has_as_member instance-of ? O 2 generates_essential_ war_materiel_from_ the_ strategic_perspective_of ? O 3 Is there any force ? O 1 that has as industrial factor an industrial capacity that generates essential war materiel from the strategic perspective of a multi-member force that includes ? O 1? 2004, G. Tecuci, Learning Agents Center instance-of US_1943 industrial_capacity has_as_industrial_factor instance-of Industrial_capacity_ multi_state_force of_US_1943 subconcept-of multi_state_ alliance subconcept-of generates_essential_ equal_partner_ war_materiel_from_ the_ multi_state_ strategic_perspective_of alliance has_as_member instance-of Allied_forces_1943

This slide illustrates how the previous question has been answered. The question is represented by the ontology fragment from the left hand side of the slide. Answering the question is equivalent with finding values for the variables from this ontology fragment. To find these values, the agent maps this ontology fragment with the agent’s ontology, as illustrated bellow. The agent attempts to match ? O 1 with US_1943. For this, it has to check that US_1943 and ? O 1 have the same features. ? O 1 is a Force. US_1943 is a single state force, which is a single-member force, which is a force. Therefore US_1943 is also a force. ? O 1 has as industrial factor ? O 2. US_1943 has as industrial factor industrial_capacity_of_US_1943. Therefore ? O 2 has to match industrial_capacity_of_US_1943. ? O 2 is an industrial capacity. Industrial_capacity_of_US_1943 is also an industrial capacity. However, ? O 2 also generates essential war materiel from the strategic perspective of ? O 3. Industrial_capacity_of_US_1943 generates essential war materiel from the strategic perspective of the Allied_Forces_1943. Therefore ? O 3 has to match Allied_Forces_1943. ? O 3 is an instance of a multi-member force and has as member ? O 1, which has previously matched with US_1943. Allied_Forces_1943 is also multi-member force and has as member US_1943. Therefore, the question: Is there any force ? O 1 that has as industrial factor an industrial capacity that generates essential war materiel from the strategic perspective of a multi-member force that includes ? O 1? Has the answer: Yes, US_1943 is a force that has as industrial factor industrial_capacity_of_US_1943 that generates essential war materiel from the strategic perspective of the Allied_Forces_1943 which is a multi-member force that includes US_1943. 2004, G. Tecuci, Learning Agents Center

Sample task A task is a representation of anything that an agent may be asked to perform. General task: Identify and test a strategic COG candidate corresponding to the ? O 1 INFORMAL STRUCTURE OF THE TASK Identify and test a strategic COG candidate corresponding to the economy of a force The economy is ? O 1 Condition ? O 1 is type_of_economy FORMAL STRUCTURE OF THE TASK Instantiated task: Identify and test a strategic COG candidate corresponding to the economy_of_US_1943 INFORMAL STRUCTURE OF THE TASK 2004, G. Tecuci, Learning Agents Center Identify and test a strategic COG candidate corresponding to the economy of a force The economy is economy_of_US_1943 FORMAL STRUCTURE OF THE TASK

Exercise How could the agent generate plausible formalizations? Identify and test a strategic COG candidate for Sicily_1943 Identify and test a strategic COG candidate for a scenario The scenario is Sicily_1943 What kind of scenario is Sicily_1943? Sicily_1943 is a war scenario Identify and test a strategic COG candidate for Sicily_1943 which is a war scenario 2004, G. Tecuci, Learning Agents Center Identify and test a strategic COG candidate for a scenario which is a war scenario The scenario is Sicily_1943

A task is a representation of anything that an agent may be asked to perform. The informal structure of a task is a phrase in free-form English with variables. The formal structure of a task contains a task name and several task features. The task name is an abstract English phrase with no variables. The task features are also phrases, but they may contain variables, such as ? O 1. The formal structure of the task contains also a condition that restricts the values that the variable can take. For example, in the case of the task from this slide, ? O 1 has to be an instance of the concept type_of_economy. Replacing the variables with objects that satisfy the condition leads to the creation of specific tasks, as illustrated at the bottom of this slide. 2004, G. Tecuci, Learning Agents Center

Sample task reduction rule A rule is an ontology-based representation of an elementary problem solving process. IF Identify and test a strategic COG candidate corresponding to the ? O 1 Question What is the type of ? O 1 ? Answer industrial_economy THEN Identify and test a strategic COG candidate corresponding to the ? O 1 which is an industrial_economy INFORMAL STRUCTURE OF THE RULE 2004, G. Tecuci, Learning Agents Center IF Identify and test a strategic COG candidate corresponding to the economy of a force The economy is ? O 1 Condition ? O 1 is industrial_economy THEN Identify and test a strategic COG candidate corresponding to the economy of a force which is an industrial economy The industrial economy is ? O 1 FORMAL STRUCTURE OF THE RULE

A rule is a representation of a generic problem-solving step. It has an informal structure and a formal structure. Let us look at the informal structure first. It should be read as follows: IF I have to perform the task Identify and test a strategic COG candidate corresponding to the ? O 1 And the question “What is the type of ? O 1 ? ” Has the answer “industrial_economy” THEN I should Identify and test a strategic COG candidate corresponding to the ? O 1 which is an industrial_economy Notice that the informal structure of the rule is very similar with the form we used to illustrate problem solving through task reduction. This is because the agent uses the informal structure to communicate with the user. To reason, the agent uses an equivalent IF-THEN formal structure. This structure indicates the condition under which the task from the IF part can be reduced to the task from the THEN part. It should be read as follows: IF I have to perform the task Identify and test a strategic COG candidate corresponding to the economy of a force, where the economy is ? O 1 And the following condition is satisfied: ? O 1 is an industrial economy THEN I should Identify and test a strategic COG candidate corresponding to the economy of a force which is an industrial economy, where the industrial economy is ? O 1 2004, G. Tecuci, Learning Agents Center

Another task reduction rule IF Identify and test a strategic COG candidate corresponding to the ? O 1 which is an industrial_economy IF Identify and test a strategic COG candidate corresponding to the economy of a force which is an industrial economy The industrial economy is ? O 1 Question Who or what is a strategically critical element with respect to the ? O 1 ? Answer ? O 2 because it is an essential generator of war_materiel for ? O 3 from the strategic perspective Condition ? O 1 is industrial_economy THEN Identify ? O 2 as a COG candidate with respect to the ? O 1 ? O 4 is force has_as_economy ? O 1 has_as_industrial_factor ? O 2 Test ? O 2 which is a strategic COG candidate with respect to the ? O 1 INFORMAL STRUCTURE OF THE RULE 2004, G. Tecuci, Learning Agents Center ? O 2 is industrial_capacity generates_essential_war_materiel_from_ the_strategic_perspective_of ? O 3 is multi_state_force has_as_member ? O 4 THEN Identify a strategically critical element as a COG candidate with respect to an industrial economy The strategically critical element is ? O 2 The industrial economy is ? O 1 Test a strategically critical element which is a strategic COG candidate with respect to an industrial economy The strategically critical element is ? O 2 The industrial economy is ? O 1

Let us consider the informal structure of this more complex rule. It should be read as follows: IF I have to perform the task Identify and test a strategic COG candidate corresponding to the ? O 1 which is an industrial economy And the question “Who or what is a strategically critical element with respect to the ? O 1 ? ” Has the answer “? O 2 because it is an essential generator of war materiel for ? O 3 from the strategic perspective” THEN I should perform the following two tasks Identify ? O 2 as a COG candidate with respect to the ? O 1 Test ? O 2 which is a strategic COG candidate with respect to the ? O 1 The formal structure should be read as follows: IF I have to perform the task Identify and test a strategic COG candidate corresponding to the economy of a force which is an industrial economy, where the industrial economy is ? O 1 And the following condition is satisfied: ? O 1 is an industrial economy, and ? O 2 is an industrial capacity that generates essential war materiel from the strategic perspective of ? O 3, and ? O 3 is a multi-state force that has ? O 4 as one of its members, and ? O 4 is a force that has as economy ? O 1, and as industrial factor ? O 2 THEN I should perform the following two tasks Identify a strategically critical element as a COG candidate with respect to an industrial economy The strategically critical element is ? O 2 The industrial economy is ? O 1 Test a strategically critical element which is a strategic COG candidate with respect to an industrial economy The strategically critical element is ? O 2 The industrial economy is ? O 1 Notice that the elements of the condition are concepts and relationships from the object ontology. 2004, G. Tecuci, Learning Agents Center

The generality of the ontology and rules Which are more general, the object descriptions from the object ontology, or the rules? 2004, G. Tecuci, Learning Agents Center

The generality of the ontology An object ontology is characteristic to an entire application domain, such as military or medicine. In the military domain the object ontology will include descriptions of military units and of military equipment. These descriptions are most likely needed in almost any specific military application. Because building the object ontology is a very complex task, it makes sense to reuse these descriptions when developing a knowledge base for another military application, rather than starting from scratch. 2004, G. Tecuci, Learning Agents Center

The generality of the rules The rules from the knowledge base are specific to a particular application and even to a particular subject matter expert. Consider, for instance, the agents discussed before, the agent that critiques courses of action with respect to the principles of war, and the agent for center of gravity analysis. While both agents need to reason with opposing forces, their reasoning rules are very different, being specific not only to their particular application (course of action critiquing versus center of gravity analysis), but also to the subject matter expertise whose knowledge they encode. 2004, G. Tecuci, Learning Agents Center

Overview Knowledge-based agents Knowledge base: Object ontology + Rules Rule-based problem solving Control of the problem solving process 2004, G. Tecuci, Learning Agents Center

Illustration of rule-based task reduction Identify and test a strategic COG candidate corresponding to the economy of a force The economy is economy_of_US_1943 ? O 1 economy_of_US_1943 Rule condition industrial_economy instance_of ? O 1 = economy_US_1943 Object ontology industrial_economy instance_of economy_US_1943 2004, G. Tecuci, Learning Agents Center IF Identify and test a strategic COG candidate corresponding to the economy of a force The economy is ? O 1 Condition ? O 1 is industrial_economy THEN Identify and test a strategic COG candidate corresponding to the economy of a force which is an industrial economy The industrial economy is ? O 1 economy_of_US_1943 Identify and test a strategic COG candidate corresponding to the economy of a force which is an industrial economy The industrial economy is economy_of_US_1943

Let us now see how the agent uses the rules in problem solving. Let us suppose that the current problem solving task is: Identify and test a strategic COG candidate corresponding to the economy of a force The economy is economy_of_US_1943 The agent will look into its knowledge base for a rule that has this type of task in the IF part. Such a rule is shown in the right hand side of the slide. As one can see, the IF task becomes identical with the task to be performed if ? O 1 is replaced with economy_of_US_1943. Next the agent has to check that the condition of the rule is satisfied for this value of ? O 1. The left hand side of the slide shows the rule’s condition. This is satisfied because the object ontology contains the information that economy_of_US_1943 is an industrial economy. Therefore the IF task can be reduced to the THEN task: Identify and test a strategic COG candidate corresponding to the economy of a force which is an industrial economy The industrial economy is economy_of_US_1943 2004, G. Tecuci, Learning Agents Center

Rule application Identify and test a strategic COG candidate corresponding to the economy_of_US_1943 ? O 1 economy_of_US_1943 IF Identify and test a strategic COG candidate corresponding to the ? O 1 What is the type of economy_of_US_1943 ? industrial_economy Question What is the type of ? O 1 ? Answer industrial_economy THEN Identify and test a strategic COG candidate corresponding to the ? O 1 which is an industrial_economy Identify and test a strategic COG candidate corresponding to the economy_of_US_1943 which is an industrial_economy 2004, G. Tecuci, Learning Agents Center ? O 1 economy_of_US_1943

As discussed before, there is also an informal structure of the rule, containing the informal structure of the tasks, a question and an answer. The right hand side of this slide shows the instantiation of the informal structure of the rule. This instantiation produces the reduction from the left hand side of the slide. Therefore, the agent can show the user the informal structure of the task reduction steps, which are in English, and therefore easier to follow. 2004, G. Tecuci, Learning Agents Center

Illustration of rule-based task reduction Identify and test a strategic COG candidate corresponding to the economy of a force which is an industrial economy The industrial economy is economy_of_US_1943 ? O 1 economy_of_US_1943 Rule condition industrial_economy instance-of force economy_of_US_1943 instance-of has_as_economy ? O 4 has_as_industrial_factor has_as_member instance-of ? O 3 Condition ? O 1 is industrial_economy ? O 2 industrial_capacity multi_state_force IF Identify and test a strategic COG candidate corresponding to the economy of a force which is an industrial economy The industrial economy is ? O 1 instance-of ? O 2 generates_essential_ war_materiel_from_ the_ strategic_perspective_of is industrial_capacity generates_essential_war_materiel_from_ the_strategic_perspective_of ? O 3 is multi_state_force has_as_member ? O 4 is force has_as_economy ? O 1 has_as_industrial_factor ? O 2 THEN Identify a strategically critical element as a COG candidate with respect to an industrial economy The strategically critical element is ? O 2 The industrial economy is ? O 1 Test a strategically critical element which is a strategic COG candidate with respect to an industrial economy The strategically critical element is ? O 2 The industrial economy is ? O 1 2004, G. Tecuci, Learning Agents Center

Let us continue the illustration of the task reduction process. The new problem solving task is: Identify and test a strategic COG candidate corresponding to the economy of a force which is an industrial economy The industrial economy is economy_of_US_1943 The agent will look in its knowledge base for a rule that has this type of task in the IF part. Such a rule is shown in the right hand side of the slide. As one can see, the IF task becomes identical with the task to be performed if ? O 1 is replaced with economy_of_US_1943. Next the agent has to check that the condition of the rule is satisfied for this value of ? O 1. The left hand side of the slide shows what conditions need to be satisfied by economy_of_US_1943, ? O 2, ? O 3 and ? O 4. This condition is satisfied if there are instances of ? O 2, ? O 3 and ? O 4 in the object ontology that satisfy all the relationships specified in the left hand side of the slide. 2004, G. Tecuci, Learning Agents Center

Matchings Object ontology Rule condition industrial_economy force single_member_force economy_of_US_1943 subconcept-of single_state_force has_as_economy ? O 4 industrial_capacity has_as_industrial_factor multi_state_force instance-of subconcept-of instance-of has_as_member force instance-of ? O 2 generates_essential_ war_materiel_from_ the_ strategic_perspective_of ? O 3 ? O 2 industrial_capacity_of_US_1943 industrial_economy instance-of economy_of_US_1943 instance-of has_as_economy US_1943 industrial_capacity has_as_industrial_factor Industrial_capacity_ multi_state_force of_US_1943 subconcept-of multi_state_ alliance subconcept-of generates_essential_ equal_partner_ war_materiel_from_ the_ multi_state_ strategic_perspective_of alliance ? O 3 Allied_forces_1943 ? O 4 US_1943 has_as_member instance-of Allied_forces_1943 2004, G. Tecuci, Learning Agents Center instance-of

The partially instantiated condition of the rule, shown in the left hand side of the slide, is matched successfully with the object ontology fragment shown in the right hand side of the slide. ? O 4 matches US_1943 because both have the same features and the corresponding values of these features also match. Both ? O 4 and US_1943 are forces. Indeed, US_1943 is an instance of a single-state force, which is a subconcept of a single-member force, which is a subconcept of a force. Therefore, using the transitivity rule discussed above, US_1943 is a force. Both ? O 4 and US_1943 have the feature has_as_economy with the value economy_of_US_1943. Finally, both ? O 4 and US_1943 have the feature has_as_industrial_factor and the corresponding values are ? O 2 and industrial_capacity_of_US_1943, respectively. Now one has to show that ? O 2 and industrial_capacity_of_US_1943 match. ? O 2 is an industrial capacity, and industrial_capacity_of_US_1943 is an industrial capacity. Both ? O 2 and industrial_capacity_of_US_1943 have the feature generates_essential_war_materiel_from_the_strategic_perspective_of, with the values ? O 3 and Allied_forces_1943, respectively. Therefore one has to show that ? O 3 and Allied_forces_1943 match. ? O 3 is a multi_state_force. Allied_forces_1943 is an equal_partner_multi_state_alliance, which is a multi_state_force. Therefore Allied_forces_1943 is also a multi_state_force. Finally, both ? O 3 and Allied_forces_1943 have the feature has_as_member with the values ? O 4 and US_1943, respectively. Moreover, ? O 4 and US_1943 have already matched. Therefore the entire matching was successful. As the result of these matching, the rule’s variables are instantiated as follows: ? O 2 industrial_capacity_of_US_1943 ? O 3 Allied_forces_1943 ? O 4 US_1943 2004, G. Tecuci, Learning Agents Center

Identify and test a strategic COG candidate corresponding to the economy of a force which is an industrial economy The industrial economy is economy_of_US_1943 Rule condition industrial_economy instance-of force economy_of_US_1943 instance-of has_as_economy ? O 4 industrial_capacity has_as_industrial_factor multi_state_force has_as_member instance-of ? O 2 generates_essential_ war_materiel_from_ the_ strategic_perspective_of ? O 1 economy_of_US_1943 IF Identify and test a strategic COG candidate corresponding to the economy of a force which is an industrial economy The industrial economy is ? O 1 Condition ? O 1 is industrial_economy ? O 2 is industrial_capacity generates_essential_war_materiel_from_ the_strategic_perspective_of ? O 3 is multi_state_force has_as_member ? O 4 is force has_as_economy ? O 1 has_as_industrial_factor ? O 2 THEN Identify a strategically critical element as a COG candidate with respect to an industrial economy The strategically critical element is ? O 2 The industrial economy is ? O 1 ? O 3 Test a strategically critical element which is a strategic COG candidate with respect to an industrial economy The strategically critical element is ? O 2 The industrial economy is ? O 1 Identify a strategically critical element as a COG candidate with respect to an industrial economy ? O 1 economy_of_US_1943 The strategically critical element is industrial_capacity_of_US_1943 The industrial economy is economy_of_US_1943 ? O 2 industrial_capacity_of_US_1943 Test a strategically critical element which is a strategic COG candidate with respect to an industrial economy The strategically critical element is industrial_capacity_of_US_1943 The industrial economy is economy_of_US_1943 2004, G. Tecuci, Learning Agents Center ? O 3 Allied_forces_1943 ? O 4 US_1943

The rule’s condition is satisfied for the following instantiations of the variables: ? O 1 economy_of_US_1943 ? O 2 industrial_capacity_of_US_1943 ? O 3 Allied_forces_1943 ? O 4 US_1943 Therefore the IF task can be reduced to the following THEN tasks: Identify a strategically critical element as a COG candidate with respect to an industrial economy The strategically critical element is industrial_capacity_of_US_1943 The industrial economy is economy_of_US_1943 Test a strategically critical element which is a strategic COG candidate with respect to an industrial economy The strategically critical element is industrial_capacity_of_US_1943 The industrial economy is economy_of_US_1943 Disciple uses the informal structure of this rule to generate the sentences to be shown to the user, as illustrated in the next slide. 2004, G. Tecuci, Learning Agents Center

Generating the informal reduction Identify and test a strategic COG candidate corresponding to the economy_of_US_1943 which is an industrial_economy ? O 1 economy_of_US_1943 IF Identify and test a strategic COG candidate corresponding to the ? O 1 which is an industrial_economy Who or what is a strategically critical element with respect to the economy_of_US_1943? industrial_capacity_of_US_1943 because it is an essential generator of war materiel for Allied_forces_1943 from the strategic perspective Identify industrial_capacity_of_US_1943 as a COG candidate with respect to the economy_of_US_1943 Test industrial_capacity_of_US_1943 which is a strategic COG candidate with respect to the economy_of_US_1943 2004, G. Tecuci, Learning Agents Center Question Who or what is a strategically critical element with respect to the ? O 1 ? Answer ? O 2 because it is an essential generator of war_materiel for ? O 3 from the strategic perspective THEN Identify ? O 2 as a COG candidate with respect to the ? O 1 Test ? O 2 which is a strategic COG candidate with respect to the ? O 1 economy_of_US_1943 ? O 2 industrial_capacity_of_US_1943 ? O 3 Allied_forces_1943 ? O 4 US_1943

Successive rule applications Identify and test a strategic COG candidate corresponding to the economy_of_US_1943 What is the type of economy_of_US_1943 ? industrial_economy Rule_2 Identify and test a strategic COG candidate corresponding to the economy_of_US_1943 which is an industrial_economy Who or what is a strategically critical element with respect to the economy_of_US_1943? industrial_capacity_of_US_1943 because it is an essential generator of war materiel for Allied_forces_1943 from the strategic perspective Identify industrial_capacity_of_US_1943 as a COG candidate with respect to the economy_of_US_1943 2004, G. Tecuci, Learning Agents Center Test industrial_capacity_of_US_1943 which is a strategic COG candidate with respect to the economy_of_US_1943 Rule_1

Task reduction rule with “Except when” conditions IF <task> Condition <condition 1> Except when condition <condition 2> Except when condition <condition n> THEN <subtask 1> … <subtask m> 2004, G. Tecuci, Learning Agents Center In addition to the regular rule condition that needs to be satisfied, a rule may contain one or several except when conditions that should not be satisfied for the rule to be applicable.

Plausible version space rule 2004, G. Tecuci, Learning Agents Center IF Identify and test a strategic COG candidate corresponding to the economy of a force which is an industrial economy The industrial economy is ? O 1 Plausible upper bound condition ? O 1 is type_of_economy ? O 2 is economic_factor generates_essential_war_materiel_from_the_strategic_perspective_of ? O 3 is multi_state_force has_as_member ? O 4 is force has_as_economy ? O 1 has_as_industrial_factor ? O 2 Plausible lower bound condition ? O 1 is industrial_economy ? O 2 is industrial_capacity generates_essential_war_materiel_from_the_strategic_perspective_of ? O 3 is multi_state_alliance has_as_member ? O 4 is single_state_force has_as_economy ? O 1 has_as_industrial_factor ? O 2 THEN Identify a strategically critical element as a COG candidate with respect to an industrial economy The strategically critical element is ? O 2 The industrial economy is ? O 1 Test a strategically critical element which is a strategic COG candidate with respect to an industrial economy The strategically critical element is ? O 2 The industrial economy is ? O 1

A rule may be partially learned. In this case it will have two applicability conditions, a plausible upper bound condition that is likely to be more general than the exact condition, and a plausible lower bound condition, that is likely to be less general than the exact condition. The plausible upper bound condition allows the rule to be applicable in many analogous situations, but the result may not be correct. The plausible lower bound condition allows the rule to be applicable fewer situations but the result is very likely to be correct. The agent will apply this rule to solve new problems and its success or failure will be used to further refine the rule. In essence, the two conditions will converge toward one another (usually through the specialization of the plausible upper bound condition and the generalization of the plausible lower bound condition), both approaching the exact applicability condition of the rule. Rule refinement could lead to a complex task reduction rule, with additional Except. When conditions which should not be satisfied in order for the rule to be applicable. 2004, G. Tecuci, Learning Agents Center

Overview Knowledge-based agents Knowledge base: Object ontology + Rules Rule-based problem solving Control of the problem solving process 2004, G. Tecuci, Learning Agents Center

Overview Knowledge-based agents An agent for center of gravity determination Problem solving through task reduction Knowledge base: Object ontology + Rules Rule-based problem solving Control of the problem solving process Tools for representation and reasoning 2004, G. Tecuci, Learning Agents Center

The search space for problem solving Let us consider the problem solving task 'Pa‘ and let R 1, R 2, and R 3 be the applicable rules which indicate the reduction of 'Pa' to ‘C(Pb, Pc)', to 'Pd', and to ‘C(Pe, Pf, Pg)', respectively. Therefore, to solve the problem 'Pa', one may either: - solve the problems 'Pb' and 'Pc', or - solve the problem 'Pd', or - solve the problems 'Pe', 'Pf' and 'Pg'. One may represent all these alternatives in the form of an AND/OR tree. 2004, G. Tecuci, Learning Agents Center

The search space for problem solving (cont. ) The node 'Pa' is called an OR node since for solving the problem 'Pa' it is enough to solve ‘C(Pb, Pc)' OR to solve 'Pd' OR to solve ‘C(Pe, Pf, Pg)'. The node ‘C(Pb, Pc)' is called an AND node since for solving it one must solve both 'Pb' AND 'Pc'. The AND/OR tree may be further developed by considering all the rules applicable to its leaves (Pb, Pc, Pd, Pe, Pf, Pg), building the entire search space for the problem 'Pa'. This space contains all the solutions to 'Pa'. 2004, G. Tecuci, Learning Agents Center

Solution tree To find a solution one needs only to build enough of the tree to demonstrate that 'Pa' is solved. Such a tree is called a solution tree. A node is solved in one of the following cases: - it is a terminal node (a primitive task with known solution); - it is an AND node whose successors are solved; - it is an OR node which has at least one solved successor. 2004, G. Tecuci, Learning Agents Center

Solution tree (cont. ) Once the problem solver detects that a node is solved it sends this information to the ancestors of the node. When the node 'Pa' becomes solved, one has found a solution to 'Pa'. solved 2004, G. Tecuci, Learning Agents Center solved

Solution tree (cont. ) A node is unsolvable in one of the following cases: - it is a nonterminal node that has no successors (i. e. a nonprimitive problem to which no rule applies); - it is an AND node which has at least one unsolvable successor; - it is an OR node which has all the successors unsolvable. 2004, G. Tecuci, Learning Agents Center

Solution tree (cont. ) Once the problem solver detects that a node is unsolvable it sends this information to the ancestors of the node. If the node 'Pa' becomes unsolvable, then no solution to 'Pa' exists. unsolvable solved 2004, G. Tecuci, Learning Agents Center unsolvable

General search strategies The presented method assumes an exhaustive search of the solution space. Usually, however, the real world problems are characterized by huge search spaces and one has to use heuristic methods in order to limit the search. What types of search control decisions can you identify? Attention focusing: What problem, among the leaves of the problem solving tree, to reduce next? Meta-rule: What rule, among the applicable ones, to use for reducing the current problem? 2004, G. Tecuci, Learning Agents Center

General search strategies Attention focusing: What problem, among the leaves of the problem solving tree, to reduce next? One may use one of the following search strategies: - breadth first search; - depth first search; - heuristic search (the heuristics establish the next problem to solve); - user directed search (the user establishes the next problem to solve), - etc. What could be a heuristic for attention focusing? 2004, G. Tecuci, Learning Agents Center

General search strategies Meta-rule: What rule, among the applicable ones, to use for reducing the current problem? The idea is to choose the rules that lead to solutions that optimize certain criteria. Could you provide some examples of meta-rules? 2004, G. Tecuci, Learning Agents Center

Search strategies in Disciple Automatic problem solver: Depth first generation of all the solutions. 1 4 2 3 Step by step problem solving: User-controlled generation of the solutions. 2004, G. Tecuci, Learning Agents Center One tries first to find solutions using the rule R 1. Only after exploring all the possible solutions using R 1 will the agent attempt to find solutions using the rule R 2, a. s. o.

General features of the hybrid representation Representational adequacy: high Inferential efficiency: medium Acquisitional efficiency: 2004, G. Tecuci, Learning Agents Center medium