Agents Mobile Agents Introduction Agents Mobile Agents Shonali

Agents & Mobile Agents Introduction – Agents & Mobile Agents ©Shonali Krishnaswamy 1

Would you bet 11 Million Euros on Mobile Agents?

Agents - The Concept § software system which acts “intelligently” on your behalf § convenient metaphor § situated in an environment and exhibit behaviour which can be viewed as: pro-active, autonomous, communicative, persistent, mobile, benevolent, adaptive/learning, collaborative, reactive, deliberative, . . . § stronger notions of agency: mentalistic notions such as knowledge, beliefs, desire, intention, goals, and a logic for reasoning with them § Cutting out the hype – a kind of software and an approach to software design

Agent Definitions • • Mission Impossible No consensus on a single definition New Buzzword Everybody wants to call their software “Agents”! • Many synonyms – just to add to the confusion • knowbots, softbots, personal assistants

What the Gurus Say… • Wooldridge and Jennings • A computer system situated in some environment • Capable of Autonomous Action to meet its design objectives in this environment • Autonomy – ability to act without direct human intervention

Objects and Agents – An Analogy • Objects encapsulate state, Agents encapsulate state + execution behaviour • Objects have no control over the execution of methods • Invocation of method m on object o – involuntary – whether object o likes it or not

Objects and Agents – An Analogy • Agents have control of whether or not to perform any given action • Request actions rather than invoke methods

Agents - Current Research and Industry § theories, architectures, languages, systems § agent (internal structure) and mult-agents (collaboration, teamwork) § still thriving research -> emerging industry § >20 companies including IBM, BT, HP, Microsoft, Fujitsu, Agent. Soft, Verity, AOS, Extempo, . . . § >40 books on “software agents” at Amazon § >50 research laboratories worldwide § organizations coordinating international agent research: Agent Society, Agent. Link, Agents-in. Melbourne

Agents - Applications § many due to: § appeal of the agent abstraction § agent research spans disciplines: artificial intelligence, distributed computing, software engineering (ABSE), sociology, psychology, economics, object-oriented systems, artificial life, game theory, . . . § a sampling. . .

The Internet and the WWW § impetus for information agents § gathering, filtering, sharing, monitoring, recommending, comparing information § guiding Web surfers § email filtering, autoresponders (e. g. , Snoop, Smartbot) § technologies: NL processing, XML/HTML, machine learning, knowledge engineering § E. g. s: Verity, Autonomy, Agent. Soft, Ci. Fi, . . .

Electronic Commerce § automate CBB stages including product advertising, product brokering, merchant brokering, negotiation, purchase and delivery, customer services § examples for brokering and negotiation: Persona. Logic, Firefly, Bargain. Finder, Jango, Kasbah, Auction. Bot, Tete-a-tete, Shop. Bot § needs: standards for unambiguous definition of commerce-related information such as goods, services, customer and business profiles, electronic forms

Business Process Management § streamline business processes in a more flexible and robust manner § e. g. : ADEPT [Jennings et al] § agents representing entities negotiate for services from each other § negotiation rules § applied to BT process for installing a network at a customer’s premises § prototypes based on mobile agents: intra- and inter-organizational workflows, supply-chain management in virtual enterprises, project management

Entertainment § visual manifestation of agent properties § e. g. s (life-like interactive animated characters): Creatures game [Grand Cliff], Extempo, Microsoft’s Persona Project (3 D, conversational parrot) § believable agents - illusion of life for objects

Pilot Training § DSTO and AAII’s SWARMM system § agents model pilot reasoning and tactics in air battle simulations § plan and meta-plan language

Manufacturing § agents systems for: § controlling manufacturing robots § managing factory production processes § e. g. : YAMS § each factory and factory component is represented by an agent § automates delegation of production orders via bidding between agents

And More. . . § agents for telecommunications: network modelling and Qo. S management § medical informatics: e. g. , multi-agent based distributed health care systems § communityware: agents represent people in virtual communities § distributed data mining

Agents - Standardization § Agent Communication Languages: § KQML, . . . § Agent Lifecycle Management, etc. . . § Organizations creating specifications: § FIPA: >40 participants including Alcatel, BT, Hitachi, NEC, Siemens, IBM, Sun Microsystems, Telia, . . . § OMG: e. g. MASIF

Important Types of Agents • • • Collaborative Interface Mobile Information / Internet Others – Reactive, Hybrid, Smart Many Classification Schemes & Typologies exist => to come in the next lecture

What is a Mobile Agent ? § Software program § Moves from machine to machine under its own control…. § Suspend execution at any point in time, transport itself to a new machine and resume execution § Once created, a mobile agent autonomously decides which locations to visit and what instructions to perform § Continuous interaction with the agent’s originating source is not required § HOW? § Implicitly specified through the agent code § Specified through a run-time modifiable itinerary

Evolution § BOTTOMLINE: Mobile Agents are a distributed computing paradigm § End point in the incremental evolution of mobile abstractions such as mobile code, mobile objects, mobile processes. § Mobile Code – transfers code § Mobile Object – transfers code + data § Mobile Process – transfers code + data + thread state § Mobile Agent – transfers code + data + thread + authority of its owner

RPC Vs Mobile Agents § Remote Procedure Calls (RPC) § One computer calls procedures on another § Messages: Requests and Responses § Procedure is “remote” – i. e. it is local to the machine that performs it § Client and Server agree in advance on the protocol for communication § Continuous on-going interaction and communication between the client and server CLIENT network SERVER

RPC Vs Mobile Agents § Instead of calling a procedure, supply the procedure as well § Messages: Mobile Agent ( procedure + data + state) § “Sending” computer may have begun the procedure and the receiving computer will continue the procedure § On-going interaction, but NO on-going communication CLIENT network Mobile Agent Service SERVER

Applets, Servlets and Mobile Agents § Applet – Downloaded from server to client § Servlet – Uploaded from client to server § Mobile Agents – Detached from client, can have multiple hops

Advantages of the Mobile Agent Paradigm § reduce bandwidth consumption and network loads § allow dynamic deployment of application components to arbitrary network sites § encapsulate protocols § execute asynchronously and autonomously § can adapt by moving § run on heterogeneous platforms § most distributed applications fit naturally into the mobile agent model § intuitively suitable for mobile users and disconnected operations § Mobile agents combine the strengths of techniques such as RPC, java applets etc. into a single, convenient framework

Mobile Agent Myths § MYTH #1: Mobile agents are risky to use. FACT #1 : No different to allowing remote access or accepting email that contains active entities § MYTH #2: Mobile agent paradigm needs a killer application to survive FACT #2: Any technology needs time to mature. Several applications rather than one killer application can also contribute towards pushing this technology further

Mobile Agent Myths § MYTH #3: Wide deployment of agent environments is unlikely to emerge…. § Because agent’s execute within a given environment. It is unlikely for such agent environments to be available on a base of computers world wide that is large enough to make MA applications truly ubiquitous

Mobile Agent Myths § FACT #3 : No …Because… § JVM’s and ORB’s exist in each browser (most MA applications are developed in Java and the OMG’s MASIF standards rely on CORBA compliant interfaces) § Development of PUSH technology can enable “uninvited” agents to execute on servers that are willing to accept them § MA toolkits are typically small in size and so are easy and inexpensive to download them on servers where they do not already exist § Emerging standards are likely to lead to “interoperable agent environments”

Mobile Agent Myths § MYTH #4: Most things that mobile agents can do, static agents can do as well § FACT #4: True…but the performance benefits associated with mobile agents can be higher

Mobile Agent Myths § MYTH #5: The Mobile Agent paradigm can solve all distributed computing issues § FACT #5: NO! Mobile Agents are not a substitute for client-server techniques. The two techniques augment each other and very often a combination of the two is the most appropriate.

Levels of Mobility § Weak Mobility § When moving a mobile agent carries code + data state § Data State - global or instance variable § On moving, execution has to start from the beginning

Levels of Mobility § Strong Mobility § When moving a mobile agent carries code + data state + execution state § Data State - global or instance variable § Execution State – local variables and threads § On moving, execution can continue from the point it stopped on the previous host

Mobile Agent Toolkits § What a DBMS is to Data, a Mobile Agent Toolkit is to Mobile Agents § Provides the infrastructure for mobile agents: § to interact with the underlying computer system – provide a “home”, a “place”, a “context” – for agents to reside in and perform their tasks on a given host § to move from host to host § to communicate with each other, with users and with host servers § to maintain privacy and integrity (of agents as well as hosts) § Current trend: Java based

Java – Lingua Franca for Mobile Agent Toolkits § BENEFITS § Platform independence § Secure execution § Dynamic class loading § Multi-threaded programming § Object serialisation

Java – Lingua Franca for Mobile Agent Toolkits § LIMITATIONS § Inadequate support for resource control § No protected references – need for a proxy object to shield access to public methods § No support for preservation and resumption of execution state

IBM’s Aglet Toolkit § An Applet-like programming model for mobile agents § Java (as many mobile agent toolkits are! ) § Aglet = Agent + Applet § Aglet’s API facilitates mobile technology § Aglet: mobile java object that visits aglet enabled hosts in a computer network § An Aglet = Instance of a Java class extending the Aglet Class

IBM’s Aglet Toolkit § An Aglet = Aglet state (values in variables) + Aglet code (class implementation) § Autonomous – runs its own thread after arriving at a host § Reactive – responds to incoming messages § Weak Mobility

IBM’s Aglet Mobile Agent System § System elements: host, engine, context, proxy, aglet § Aglet Transfer Protocol e. g. “atp: //hostname: port/context/” § Aglet. ID: system-given globally unique identifier for life

IBM’s Aglet Mobile Agent System user proxy aglet context proxy aglet engine host

IBM’s Aglet System § Proxy: representative of an aglet. § Shields and protects an aglet from direct access to its public methods § Provides location transparency for the object Context: an aglet’s work place. § § § A server can have several contexts. Named Stationary Message: objects exchanged between aglets § Synchronous and Asynchronous messaging (using FUTURE REPLY)

The Aglet Model § Operations on aglets: § creation – within a context. Assign id, initialise and execute. § run § cloning – identical copy in the same context. Different id and execution thread § dispatching – move from one context to another where execution will restart (i. e. threads do not migrate) § retraction – pull from current context and insert into the context from which retraction was requested

The Aglet Model § activation & deactivation – temporary halt and store in secondary storage § disposal – halt execution and remove from current context § Event-based control via user-defined methods: on. Creation, on. Disposing, on. Cloning, on. Dispatching, on. Reverting, on. Arrival, on. Activation, on. Deactivating, … § Messaging between aglets: messaging via proxy, a message invokes a method

Several Other Toolkits § § § Gossip - Tryllian Grasshopper – IKV++ Technologies D’Agents - Dartmouth University Voyager - Object. Space MOA - Mobile Objects and Agents - The Open Group Research Institute § Concordia - Mitsubishi Electric Lab § JSeal, Gypsy, Gossip – Many, many more…

Mobile Agent Applications § WWW Information Retrieval § Electronic Marketplace § Distributed Data Mining § Mobile Computing § Space Presence § Others – Network Management, Distributed Database Access

Mobile Web Robots/Spiders § Send mobile agents to the server side to search/filter through web pages and send only the relevant pages (or parts of pages) back § Deploy mobile agents to index web pages – analyse and construct partial indexes on the server side –and send back the index

Mobile Web Robots/Spiders § § § Effective use of internet bandwidth Better performance Filtering of data and avoiding transfer of intermediate data § Better load distribution § Continue scanning and screening even if the link goes down

Electronic Marketplace § Widely quoted application domain for mobile agents § Electronic Marketplace: Suppliers, Dealers, Buyers and Brokers § Buyers are generally the most benefited by mobile agents § Transaction Phases § Information Phase – buyer collects information from many prospective suppliers § Negotiation Phase – buyer and supplier negotiate the conditions of the transaction § Execution Phase – Actual exchange of goods

Electronic Marketplace § Market Structures § Direct Search Markets § Buyer directly contacts different suppliers § Buyer has to perform the entire information phase § Time consuming and expensive § Mobile Agents are ideally suited to perform the search

Electronic Marketplace § Brokered Markets § Brokers perform the search for a certain fee § Here brokers use mobile agents instead of the buyers § Dealer Markets § Dealers are required to buy products in advance and offer them at set prices to buyers § Buyer asks different dealers for prices and immediately buys the product at the cheapest dealer § Mobile agents can be used to find the cheapest price offered

MA Applications: Electronic Marketplace § Auction Markets § Centralise supplies and demands on a single virtual market place § Less need for mobile agents as suppliers and buyers can see the potential trading partners

Electronic Marketplace § Information Phase : Mobile agents are very useful and very easy to use, definite performance benefit § Negotiation Phase : Mobile agents can be used to reduce traffic, but there is more complexity involved in negotiation than in mere searching. Intelligent Mobile Agents? Also increased security requirements § Execution Phase : Mobile agents can be used if the transaction involves digital goods. However, agent needs to carry digital cash and sign on behalf of the user. How much do you trust your agent ?

Distributed Data Mining § Data Mining (DM): Discovery of hitherto unknown patterns from very large databases § Distributed Data Mining (DDM): Data mining of distributed data sources § Characteristics: § Distribution of data, users, mining algorithms and computational resources § Heterogeneity of data § Large data volumes § DDM = DM + Knowledge Integration

Distributed Data Mining § Client Server Model for DDM: Bring data from distributed sources into a data mining server for mining. § Disadvantage: Communication Overhead § Mobile Agent Model: Dispatch mining agents to the distributed data sites. § Overcomes the communication bottleneck § But the problem of non-dedicated computational resources § Our Work – Hybrid DDM Model

Delivering Services to Mobile Devices § Environment: a set of wireless/wired networked mobile/fixed computers § dynamic environment: computational resources, battery power, memory, bandwidth (with frequent disconnections) limited and varying for the same computer and across computers; set of computers in a domain varying § some uses of mobile software/agents: § move/off-load (multiple) computations to other sites (e. g. , processing at database, Web and WAP servers): no need to maintain connection, depleting resources, move to discovered resources § software components only when and where needed: cope with limited memory, zero-maintenance mobile computers, different versions for different hardware characteristics

Delivering Services to Mobile Devices § user’s service environment can follow user’s mobile device (e. g. , VHE, Net. Chaser) § agents move to mobile devices to perform tasks (e. g. , monitor and gather information from deployed mobile devices) § research: mobile places, docking stations e. g. SOMA, Agent. Tcl, MASE (ACTS CLIMATE), Magenta, Tacoma, Discovery

Current Areas of Work § mobile agent theories: Pi-calculus extensions, Mobile Ambients, Agent Itineraries § mobile agent model: some component-based, AI -based § mobile agent infrastructure: environment supporting mobile agents - security, naming, domain crossing, etc § mobile agent programming: languages, toolkits, abstractions § mobile agent applications: mobile agent standards: OMG’s MASIF, FIPA

Research Issues § Security: protect host from agents, protect agents from host § Performance: if Java or Python, performance penalities with interpretation (esp. for performance critical applications), but not for long? § Strong mobility: move full execution state (stacks etc), stacks not accessible with current Java? § MA management: § how control and manage deployed agents § issues: fault tolerance (e. g. , agent fails, host fails), recalling agents, tracking agents, servicing agents (esp. longer living agents)