Simulating Emergent Cognition in Artificial Life

Júlio L. R. Monteiro (Ph.D student)Advisor: Marcio Lobo NettoUniversity of São Paulo - BrazilCognitio Research Group

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Summary

1. Introduction2. Objectives3. Methodology4. Environmental Model5. Creature Model6. Cognition Model7. Expected Results

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1. Introduction

Life can be understood as:Open, associative systemSelf-organized, autonomousEvolutive, learning from past experiencesHierarchical, with many complexity levels

Life is a system to preserve information against natural decay[ADAMI’88]

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2. Objectives

Observe the emergence and evolution of complex cognitive processes in virtual life creatures, such as:Learning from experienceDevelopment of strategies (planning)Abstraction of concepts Attention

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3. Methodology

Develop an interactive computer simulator:Simple but extensible universe modelArtificial life creatures, with virtual DNAEvolutive cognitive model

Design experiments and observe “state shift” situations

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4. Environmental Model

3D universe Basic entities are colored geometric solids Basic Properties:

Color (visible state)Energy (internal state)Shape (function)Mass (integrity, inertia)

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Example Entities

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Universal Dynamics

MovementCollisionGravityEnergy conversion (via Effectors)

Energy TransferEmittersReceptors

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5. Creature Model

A creature develops many subsystems: Conjunctive Perceptive Effective Cognitive Reproductive

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Conjunctive System

Implements the creature’s main body Holds information related to:

Energy reservesPhysical integritySockets to other subsystems

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Perceptive System

Responsible for the identification of other entities and their attributes

Typical perceptors:ColorShapeEnergyDistance

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Effective System

Allows creatures to interact with the environment

Typical effectors:MovementEnergy emittersGrapplers

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Cognitive System

Allows complex control of behavior Filters the input from the Perceptive system Builds an internal representation of the universe Relays commands to the Effective System Implemented using the Memory Evolutive

System [EHRESMANN’02]

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Reproductive System

Allows the production of other entities or creatures

Creatures have Metastrings as virtual DNA Many Metastrings can be stored together

and used at different stages

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Metastrings

A special kind of meta-entities with no volume or mass, that represents recipes for building any possible entity

Uses hierarchical categories [EILENBERG’45]

Can be as detailed as needed Mutation occurs more frequently in lower

hierarchical levels

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Metastring example

CREATURE

EFFECTOR_2

EFFECTOR_1

PERCEPTOR_1

SHAPE

SOCKET_3

SOCKET_2

SOCKET_1

COGNITOR

EFFECTIVE

PERCEPTIVE

COGNITIVE

PERCECTOR_2

CONJUNTIVE

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6. Cognition Model

Based on the Memory Evolutive System model[EHRESMANN’02]

Described as a category graph with Interconnected agents in various hierarchical complexity levels

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MES and Complexity

Agents in a higher level have a representation as a distinguished pattern in the lower level (colimit)

The existence of multi-fold objects justifies implies complex links that can’t be expressed in lower levels

[EHRESMANN’05]

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MES in Detail

Composed of local hierarchical Centers of Regulation (CRs)

Each CRs operates in different timescales, developing a stepwise process: Formation of the actual landscape Selection of a strategy based on the Memory Building an anticipated landscape Command effectors to realize the strategy Evaluate and memorize the results

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MES in Detail

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7. Expected Results

Some points of interest are:Formation of a multilayered memory:

Empirical (storing all sensorial stimuli) Experiential (storing causal relations) Procedural (storing recombined strategies) Semantic (allows abstraction of concepts)

Group behavior (competition / alliance)Design of a genetic language

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Expected Results

The chosen model allows for the gradual increase in detail in the description of the environment

Evolution can be measured in species and creature memory

Precise experimental setups still need to be formulated

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References

ADAMI, C. (1988) Introduction to Artificial Life, Springer, New York.

EHRESMANN, A.; VANBREMEERSCH, J.-P. (2002) Emergence Processes up to Consciousness Using the Multiplicity Principle and Quantum Physics. In: Proc. AIP Conference, V. 627, I. 1, pp. 221-233

EHRESMANN, A.; VANBREMEERSCH, J.-P. (2005) Memory Evolutive Systems Homepage, Amiens, FR: http://perso.wanadoo.fr/vbm-ehr/, visited in July, 10, 2005

EILENBERG, S.; MAC LANE, S. (1945) General theory of natural equivalences. In: Trans. AMS 58, p. 231-294.