Agent Societies and Artificial Intelligence

Very recent articles have addressed the problem of the interaction between populations of virtual robots. Vijayakumar and Davis ("Metacognition in a "society of mind"") investigate the concept of mind as a control system using the "Society of Mind" idea from Marvin Minsky. They develop Metacognition in a model based on the differentiation between metacognitive strategies. Metacontrol is a part of metacognition. The authors explore Metacognition mechanisms in developing optimal agents for the fungus world testbed. The fungus world environment allows the behaviours of a robot to be monitored, measured and compared. It is generated a swarm intelligence of how the group of agents work together to achieve a common goal. Vijayakumar and Davis implement an architecture with six layers including reflexive, reactive, deliberative, learning, metacontrol and metacognition layers. The authors design an experiment with different types of agents (random, reflexive, reactive...) All agents move in the environment, changing direction in case of obstacles. To compare the results of each agent, the following data were collected: life expectancy, fungus consumption, resource collection and metabolism. Total performance was denoted by the combination of resource collected and life expectancy. Experiments were conducted for each type of agent. In Simulation 1, deliberative agents collected 50% of resource and left 64% of energy. In Simulation 2, the results of deliberative agents were compared to Metacognition agents, collecting metacognitive agents 82% of resource and lefting 71% of energy. The result concludes that Metacognition agents are better than other cognition and deliberative agents. Thus, Metacognition is a very powerful tool for control and self-reflection and intelligent and optimal agents can be viewed as collective behaviours as a "Society of Mind". Really to develop a Metacognition concept in Artificial Intelligence seems necessary for building self configurable computational models and true intelligence.