1. Cognitive Architectures and General Intelligent Systems Pay Langley 2006 Presentation : Suwang Jang

2. Index  A trend of AI  Original Goal of AI and modern AI  Three Architectural Paradigms  Multi-agent systems  Blackboard systems  Cognitive Architecture  Commitments of Cognitive Architecture  ICARUS Architecture  Memories and Representations  Performance and Learning Process

3. Envision by early AI researchers  The Original Goal of AI was constructing artifacts which have almost same intellectual capacity as humans ☞ General Intelligent Systems

4. But, Modern AI? Computer vision Computational linguistics Planning ……. - Fragmented Approaches -

5. Newell’s arguments (1973)  He was critiquing the strategy of experimental cognitive psychologists, who studied isolated components of human cognition without considering their interaction ? ? !!  And he argued that we should evaluate AI in terms of generality and flexibility, rather than success on a single domain

6. The Notion of Newell  Cognitive Psychology + (as close allies)  AI Research ☞ “Cognitive Architecture” (1973)

7. Three Architectural Paradigms for General Intelligent System  Multi-agent System  Blackboard System  ACT, Soar and I CARUS (Cognitive Architecture Based)

8. Multi-agent System (Sycara 1998)  Traditional approaches to software engineering  Features  Distinct modules  Direct communication with each other (Specified Input/Output and Protocol)  No constraints on how each module operates  Advantage  Easy for teamwork (Developing each module separately and Integrating them)  Disadvantage  Need for modules to communicate directly with one another

9. Blackboard System (Engelmore and Morgan 1989)  Retains Modularity of the first framework  Indirect Communication through short-term memory  More closer to theories of human cognition Pattern matching against elements

10. Newell’s View  Unified theory of intelligent behavior, not simply integrated one  Mutual constraints for independency among modules  Architectural design changed only gradually for correspondence to new structure that supporting new functionality

11. Cognitive Architecture  The short-term and long-term memories that store the agent’s beliefs, goals, and knowledge  The representation and organization of structures that are embedded in these memories  The functional processes that operate on these structures, including both performance and learning mechanisms  A programming language that lets one construct knowledge-based systems that embody the architecture’s assumption

12. The I CARUS Architecture  Common cognitive architecture + concern with physical agent that operate in an external environment

13. Principles  Cognition is grounded in perception and action  Concepts and skills are distinct cognitive structures  Long-term memory is organized in a hierarchical fashion  Skill and concept hierarchies are acquired in a cumulative manner  Long-term and short-term structures have a strong correspondence

14. Memories and Representations ① ② ③ ④ ⑤

15. ① Conceptual Memory  Concept :  Head ☞ name arguments  Body  :percept ☞ type, attribute value (from Perceptual Buffer)  :relation ☞ low-level concept  :test (primitive concept) ☞ Boolean test  Bottom-up

16. Primitive Non-Primitive Long-term concept memory

17. ② Skill Memory  Primitive skill :  Head ☞ Concept which the clause should achieve upon successful completion  Body  :start ☞ describe the situation in which the agent initiate the clause  :require ☞ field that must hold throughout execution  :actions ☞ executable action (to Motor Buffer)

18. ② Skill Memory  Non-primitive skill :  No :require field and :action field  Instead have a :subgoals field  Top-down

19. Primitive Non-Primitive Recursive Call Long-term skill memory

20. Short-term Memory  ③ Belief memory  (Concept name + Instance)  ④ Perceptual buffer  (type, unique name, attribute + value …)  ⑤ Goal/Intention Memory  Stack of goals … Sub goal High-level goal

21. Short-term belief memory

22. Short-term perceptual buffer

23. Performance and Learning Processes

24. Conceptual Clause (Left) and Skill Clause (Right)

25. Skill Clause  Top-down manner  If execution module can find an applicable path, it carry out actions.  Applicable path :  Concept instance of goal is not satisfied yet  Requirements of terminal skill are satisfied  For each skill instance in the path not executed on the previous cycle  The start conditions are satisfied

26. Skill Clause  If execution module can not find applicable path It evokes a module for Means-ends problem solving (Newell and Simon 1961)  Push new goals and concept definition needed to achieve top-level goal onto goal stack until it find one it can achieve with an applicable skill  Applicable skill -> pop  Unsatisfied concept -> push sub-concepts  If none remain -> pop the parent  This processes continues until system achieve top-level goal

27. Learning  A learning module creates a new skill whenever problem solving  Achieved goal + subgoals as subskills + start condition  It discussed in more detail elsewhere (Langley and Choi, 2006)

28. Simulation of In-city driving  ICARUS program for delivering packages in simulated driving environment  Simulated environment  buildings, road segments, intersections, lane lines, packages, other vehicles, and agents’ vehicles  15 primitive concepts and 55 higher-level concepts (6 level deep)  8 primitive skills and 33 higher-level skills (5 level deep)  Result : Changing speed, altering wheel angle, depositing packages