0000000000709827
AUTHOR
Giuseppe Sajeva
A hybrid architecture for autonomous agents
A new hybrid approach for autonomous agents is described. The approach integrates in a principled way the functional and the behavioral approaches of agent design. The integration is based on the introduction of a conceptual space representation that links the subsymbolic level, which is a repository of reactive modules, with the symbolic level, in which rich symbolic descriptions of the agent environment take place. Results are reported obtained by an experimental implementation of the agent.
An ASSOM neural network to represent actions performed by an autonomous agent
An ASSOM neural network to describe the action performed by an autonomous reactive agent is proposed. The neural network receives in input the sequences of data acquired by the agent internal sensors and it classifies them by generating the corresponding symbolic assertions. Experimental results performed on a RWI B12 autonomous robot are reported.