IV Flashcards
Main aspects of Cognitivist modelling approaches
inferencing mechanisms, representations, rationality, problem solving
Architectures of cognitivist approach
SOAR, EPIC, ACT-R, …
Problems of cognitivist modelling approach
Grounding Problem: Connection to the environment
Main aspects emergent modelling approach
robust routine behaviour, understanding and exploitation of coupling to the environment
Problem of Emergent Modelling approach
Autonomy problem - separation from one’s environment
How should/shouldn’t we obtain a unified theory of cognition?
Not: divide-and-conquer - highly specific theories of very limited range of phenomena
But: Focus on integrative work= cognitive architectures
= include attention, memory, problem solving, decision making, learning
Typical Application area of unified theories of cognition
human-machine interaction
A wide range of cognitive capabilities are employed in “even simple” tasks
Characteristics for AGI Environments, Tasks, and Agents
- Complex dynamic open environment; diverse, interacting, richly structured objects
- Task-relevant regularities at multiple time scales
- Other agents impact performance
- Complex, diverse, novel tasks
- Interactions between agent, environment and tasks are complex and limited
- Computational resources of the agent are limited
- Agent existence is long-term and continual
Cognitive Architecture Requirements
New tasks do not require agent re-programming
•Realize a symbol system
•Represent and effectively use knowledge: modality-specific, diverse levels, large bodies, different levels of generality; beliefs independent of current perception; rich hierarchical control, meta-cognitive
•Support a spectrum of bounded and unbounded deliberation
•Support diverse, comprehensive learning and incremental, online learning
AGI: Full Development Theories
Vygotsky….
Piaget….
Substrata for AGI Landscape (Adams et. al, 2011)
Information processing - Implementation Metaphor
Math - Information Theory: formal definitions of intelligence, intelligence as compression
Physiology - Existing Realization: Insights from bioscience, universal aspects of development
Challenge or AGI Landscape
finding tasks and environments
Cognition implies…..
ability to understand how things might possibly be, now or at some future time
… using the past to predict the future (memory, anticipation)
… assimilating what does actually happen to adapt and improve anticipatory abilities
Cognition breaks free of the present
A cognitive system…
can function effectively under circumstances that were not planned for explicitly when the system was designed
Plasticity, resilience in the face of the unexpected
… can explain what it is doing and why it is doing it
Identification of potential problems, recognise need for new information
… can view a problem in more than one way and use knowledge about itself and the environment
Self-reflection
Traditional assumption of cognition
planning dominates over execution
Failing -> plan repair -> continuous planning and erring
Characteristics of traditional assumption
Boundedness, limited autonomy, multiple goals/tasks
–Bird-eye’s view first person point of view
–From full top-down control (“goal”, “plan”) towards perceptually coordinated activity ()
–Motivated configuration and interpretation of sensory-motor couplings to the world
–Distinction of subjective concerns from “goals”
•Persistence, social environment
–History matters! Adaptivity, individuality,… personae
New assumption
Offline certainties & reifications, closed worlds online qualities & dynamics, open worlds
Short summary of Cognitivist approach
Based on symbolic information processing representational systems
•“Cognition as type of computation” defined on symbolic representations
•Representations instantiated physically as cognitive codes
•Behaviour is a causal consequence of operations on these codes
•Cognition as symbolic, rational, encapsulated, structured, algorithmic
Short summary of Emergent System
- Emphasis on principles of self-organisation, emergence
- Dynamical systems view
- Connectionist systems, Enactive systems
Short summary of Hybrid Models
•Focus on perception-action behaviours rather than perceptual abstraction of representations
Modelling Approaches of Cognitivist, deliberative, reflective, symbolic
–Main aspects: inferencing mechanisms, representations, rationality, problem solving
–Cf. Folk Psychology/Theory Theory
–Well-known architectures:
•SOAR, EPIC, ACT-R, …
Grounding problem: Connecting to the “environment”