March 2008 7 Principles of Synthetic Intelligence Joscha

March 2008 7 Principles of Synthetic Intelligence Joscha Bach, University of Osnabrück, Cognitive Science March 1 st, 2008

AGI 08 What is Artificial General Intelligence up to? Perception, and what depends on it, is inexplicable in a mechanical way, that is, using figures and motions. Suppose there would be a machine, so arranged as to bring forth thoughts, experiences and perceptions; it would then certainly be possible to imagine it to be proportionally enlarged, in such a way as to allow entering it, like into a mill. This presupposed, one will not find anything upon its examination besides individual parts, pushing each other— and never anything by which a perception could be explained. (Gottfried Wilhelm Leibniz 1714) March 1 st, 2008 2

AGI 08 What is Artificial General Intelligence up to? Perception, and what depends on it, is inexplicable in a mechanical way, that is, using figures and motions. Suppose there would be a machine, so arranged as to bring forth thoughts, experiences and perceptions; it would then certainly be possible to imagine it to be proportionally enlarged, in such a way as to allow entering it, like into a mill. This presupposed, one will not find anything upon its examination besides individual parts, pushing each other— and never anything by which a perception could be explained. (Gottfried Wilhelm Leibniz 1714) March 1 st, 2008 3

AGI 08 AI Scepticism: G. W. Leibniz Perception, and what depends on it, is inexplicable in a mechanical way, that is, using figures and motions. March 1 st, 2008 4

AGI 08 AI Scepticism: Roger Penrose The quality of understanding and feeling possessed by human beings is not something that can be simulated computationally. Perception, and what depends on it, is inexplicable in a mechanical way, that is, using figures and motions. March 1 st, 2008 5

AGI 08 AI Scepticism: John R. Searle Syntax by itself is neither The quality of understanding and constitutive of nor sufficient for feeling possessed by human beings is semantics. not something that can be simulated Computers only do syntax, so computationally. Perception, and what depends on it, they can never understand is inexplicable in a mechanical way, anything. that is, using figures and motions. March 1 st, 2008 6

AGI 08 AI Scepticism: Joseph Weizenbaum Syntax by itself is neither The quality of understanding and constitutive of nor sufficient for feeling possessed by human beings is semantics. not something that can be simulated Computers only is do syntax, so Human experience computationally. Perception, and what depends on it, they can never understand not transferable. (…) is inexplicable in a mechanical way, anything. Computersthat canis, not befigures and motions. using creative. March 1 st, 2008 7

AGI 08 AI Scepticism: General Consensus… Syntax by itself is neither The quality of understanding and Computers can not, constitutive of nor sufficient for feeling possessed by human beings is semantics. because they should not something that can be simulated Computers only doissyntax, so Human experience computationally. Perception, and what depends on it, The “Winter of AI” they can never understand not transferable. (…) is inexplicable in a mechanical way, anything. is far from over. Computers can be figures and motions. thatnot is, using creative. March 1 st, 2008 8

AGI 08 AI is not only trapped by cultural opposition AI suffers from - paradigmatic fog - methodologism - lack of unified architectures - too much ungrounded, symbolic modeling - too much non-intelligent, robotic programming - lack of integration of motivation and representation - lack of conviction March 1 st, 2008 9

AGI 08 Lessons for Synthesizing Intelligence 1. Build whole, functionalist architectures March 1 st, 2008 10

AGI 08 Lessons for Synthesizing Intelligence 1. Build whole, functionalist architectures (infrared) imaging of combustion engine March 1 st, 2008 11

AGI 08 Lessons for Synthesizing Intelligence 1. Build whole, functionalist architectures (infrared) imaging of combustion engine March 1 st, 2008 12

AGI 08 Lessons for Synthesizing Intelligence 1. Build whole, functionalist architectures March 1 st, 2008 13

AGI 08 Lessons for Synthesizing Intelligence 1. Build whole, functionalist architectures Requirement: Dissection of system into parts and relationships between them March 1 st, 2008 14

AGI 08 #1: Build functionalist architectures Requirement: Dissection of system into parts and relationships between them March 1 st, 2008 15

AGI 08 Lessons for Synthesizing Intelligence 1. Build whole, functionalist architectures 2. Let the question define the method March 1 st, 2008 16

AGI 08 Lessons for Synthesizing Intelligence 1. Build whole, functionalist architectures 2. Let the question define the method – not vice versa! AI‘s specialized sub-disciplines will not be re-integrated into a whole. March 1 st, 2008 17

AGI 08 Lessons for Synthesizing Intelligence 1. Build whole, functionalist architectures 2. Let the question define the method 3. Aim for the Big Picture, not narrow solutions March 1 st, 2008 18

AGI 08 Conceptual Analysis: HCog. Aff (Sloman 2001) March 1 st, 2008 19

AGI 08 Lessons for Synthesizing Intelligence 1. Build whole, functionalist architectures 2. Let the question define the method 3. Aim for the Big Picture, not narrow solutions 4. Build grounded systems March 1 st, 2008 20

AGI 08 Lessons for Synthesizing Intelligence 1. Build whole, functionalist architectures 2. Let the question define the method 3. Aim for the Big Picture, not narrow solutions 4. Build grounded systems – but do not get entangled in the „Symbol Grounding Problem“ The meaning of a concept is equivalent to an adequate encoding over environmental patterns. March 1 st, 2008 21

AGI 08 Modal vs. amodal representation (Barsalou 99) March 1 st, 2008 22

AGI 08 Lessons for Synthesizing Intelligence 1. Build whole, functionalist architectures 2. Let the question define the method 3. Aim for the Big Picture, not narrow solutions 4. Build grounded systems 5. Do not wait for robots to provide embodiment March 1 st, 2008 23

AGI 08 Lessons for Synthesizing Intelligence 1. Build whole, functionalist architectures 2. Let the question define the method 3. Aim for the Big Picture, not narrow solutions 4. Build grounded systems 5. Do not wait for robots to provide embodiment – Robotic embodiment is costly, but not necessarily more “real” than virtual embodiment. March 1 st, 2008 24

AGI 08 March 1 st, 2008 25

AGI 08 Lessons for Synthesizing Intelligence 1. Build whole, functionalist architectures 2. Let the question define the method 3. Aim for the Big Picture, not narrow solutions 4. Build grounded systems 5. Do not wait for robots to provide embodiment 6. Build autonomous systems March 1 st, 2008 26

AGI 08 Lessons for Synthesizing Intelligence 1. Build whole, functionalist architectures 2. Let the question define the method 3. Aim for the Big Picture, not narrow solutions 4. Build grounded systems 5. Do not wait for robots to provide embodiment 6. Build autonomous systems Intelligence is an answer to serving polythematic goals, by unspecified means, in an open environment. Integrate motivation and emotion into the model. March 1 st, 2008 27

AGI 08 Lessons for Synthesizing Intelligence 1. Build whole, functionalist architectures 2. Let the question define the method 3. Aim for the Big Picture, not narrow solutions 4. Build grounded systems 5. Do not wait for robots to provide embodiment 6. Build autonomous systems 7. Intelligence is not going to simply “emerge” March 1 st, 2008 28

AGI 08 Lessons for Synthesizing Intelligence 1. Build whole, functionalist architectures 2. Let the question define the method 3. Aim for the Big Picture, not narrow solutions 4. Build grounded systems 5. Do not wait for robots to provide embodiment 6. Build autonomous systems 7. Intelligence is not going to simply “emerge”: Sociality, personhood, experience, consciousness, emotion, motivation will have to be conceptually decomposed and their components and functional mechanisms realized. March 1 st, 2008 29

AGI 08 Taking the Lessons: Micro. Psi • Integrated architecture, based on a theory originating in psychology • Unified neuro-symbolic representation (hierarchical spreading activation networks) • Functional modeling of emotion: – – Emotion as cognitive configuration Emotional moderators • Functional modeling of motivation: – – – Modeling autonomous behavior Cognitive and Physiological drives Integrating motivational relevance with perception/memory March 1 st, 2008 30

AGI 08 Implementation: Micro. Psi (Bach 03, 05, 04, 06) March 1 st, 2008 31

AGI 08 Implementation: Micro. Psi (Bach 03, 05, 04, 06) Low-level perception March 1 st, 2008 32

AGI 08 Implementation: Micro. Psi (Bach 03, 05, 04, 06) Low-level perception Control and simulation March 1 st, 2008 33

AGI 08 Implementation: Micro. Psi (Bach 03, 05, 04, 06) Low-level perception Multi-agent interaction March 1 st, 2008 Control and simulation 34

AGI 08 Implementation: Micro. Psi (Bach 03, 04, 05, 06) Robot control Multi-agent interaction March 1 st, 2008 Low-level perception Control and simulation 35

AGI 08 Foundation of Micro. Psi: PSI theory (Dörner 99, 02) How can the different aspects of cognition be realized? March 1 st, 2008 36

AGI 08 PSI theory (Dörner 99, 02) March 1 st, 2008 37

AGI 08 PSI theory (Dörner 99, 02) March 1 st, 2008 38

AGI 08 PSI theory (Dörner 99, 02) March 1 st, 2008 39

AGI 08 PSI theory (Dörner 99, 02) March 1 st, 2008 40

AGI 08 Motivation in PSI/Micro. Psi March 1 st, 2008 41

AGI 08 Integrated representation March 1 st, 2008 42

AGI 08 Goal of Micro. Psi: broad model of cognition Aim at • Perceptual symbol system approach • Integrating goal-setting • Use motivational and emotional system as integral part of addressing mental representation • Physiological, physical and social demands and affordances • Modulation/moderation of cognition March 1 st, 2008 43

AGI 08 Lessons for Synthesizing Intelligence 1. Build whole, functionalist architectures 2. Let the question define the method 3. Aim for the Big Picture, not narrow solutions 4. Build grounded systems 5. Do not wait for robots to provide embodiment 6. Build autonomous systems 7. Intelligence is not going to simply “emerge” Website: www. cognitive-agents. org • Publications, • Download of Agent, • Information for Developers March 1 st, 2008 44

AGI 08 … and this is where it starts. Thank you! Website: www. cognitive-agents. org • Publications, • Download of Agent, • Information for Developers March 1 st, 2008 45

AGI 08 Many thanks to… - the Institute for Cognitive Science at the University of Osnabrück and the AI department at Humboldt-University of Berlin for making this work possible - Ronnie Vuine, David Salz, Matthias Füssel, Daniel Küstner, Colin Bauer, Julia Böttcher, Markus Dietzsch, Caryn Hein, Priska Herger, Stan James, Mario Negrello, Svetlana Polushkina, Stefan Schneider, Frank Schumann, Nora Toussaint, Cliodhna Quigley, Hagen Zahn, Henning Zahn and Yufan Zhao for contributions March 1 st, 2008 46

AGI 08 Motivation in PSI/Micro. Psi March 1 st, 2008 47

AGI 08 Modulation in PSI/Micro. Psi March 1 st, 2008 48

AGI 08 Motivation in PSI/Micro. Psi Urges/drives: – – Finite set of primary, pre-defined urges (drives) All goals of the system are associated with the satisfaction of an urge including abstract problem solving, aesthetics, social relationships and altruistic behavior – Urges reflect demands – Categories: physiological urges (food, water, integrity) social urges (affiliation, internal legitimacy) cognitive urges (reduction of uncertainty, and competence) March 1 st, 2008 49

AGI 08 Emotion in PSI/Micro. Psi Lower emotional level (affects): – – – Not independent sub-system, but aspect of cognition Emotions are emergent property of the modulation of perception, behavior and cognitive processing Phenomenal qualities of emotion are due to effect of modulatory settings on perception on cognitive functioning experience of accompanying physical sensations (Higher level) emotions: – – Directed affects Objects of affects are given by motivational system March 1 st, 2008 50