Simulating Emergent Cognition in Artificial Life Júlio L. R. Monteiro (Ph.D student) Advisor: Marcio Lobo Netto University of São Paulo - Brazil Cognitio Research Group

2 Summary 1. Introduction 2. Objectives 3. Methodology 4. Environmental Model 5. Creature Model 6. Cognition Model 7. Expected Results

3 1. Introduction Life can be understood as:  Open, associative system  Self-organized, autonomous  Evolutive, learning from past experiences  Hierarchical, with many complexity levels Life is a system to preserve information against natural decay [ADAMI’88]

4 2. Objectives Observe the emergence and evolution of complex cognitive processes in virtual life creatures, such as:  Learning from experience  Development of strategies (planning)  Abstraction of concepts  Attention

5 3. Methodology Develop an interactive computer simulator:  Simple but extensible universe model  Artificial life creatures, with virtual DNA  Evolutive cognitive model Design experiments and observe “state shift” situations

6 4. Environmental Model 3D universe Basic entities are colored geometric solids Basic Properties:  Color (visible state)  Energy (internal state)  Shape (function)  Mass (integrity, inertia)

7 Example Entities

8 Universal Dynamics Movement  Collision  Gravity  Energy conversion (via Effectors) Energy Transfer  Emitters  Receptors

9 5. Creature Model A creature develops many subsystems:  Conjunctive  Perceptive  Effective  Cognitive  Reproductive

10 Conjunctive System Implements the creature’s main body Holds information related to:  Energy reserves  Physical integrity  Sockets to other subsystems

11 Perceptive System Responsible for the identification of other entities and their attributes Typical perceptors:  Color  Shape  Energy  Distance

12 Effective System Allows creatures to interact with the environment Typical effectors:  Movement  Energy emitters  Grapplers

13 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]

14 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

15 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

16 Metastring example CREATURE EFFECTOR_2 EFFECTOR_1 PERCEPTOR_1 SHAPE SOCKET_3 SOCKET_2 SOCKET_1 COGNITOR EFFECTIVE PERCEPTIVE COGNITIVE PERCECTOR_2 CONJUNTIVE

17 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

18 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]

19 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

20 MES in Detail

21 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

22 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

23 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 EHRESMANN, A.; VANBREMEERSCH, J.-P. (2005) Memory Evolutive Systems Homepage, Amiens, FR: visited in July, 10, 2005 EILENBERG, S.; MAC LANE, S. (1945) General theory of natural equivalences. In: Trans. AMS 58, p