Cognitive Agents Learning by Communicating
Abstract
Cognitive Agent communication is a research field in full development. We propose here an extension and an implementation of the STROBE model, which regards the Agents as Scheme interpreters. These Agents are able to interpret messages in a dedicated environment including an interpreter that learns from the current conversation. These interpreters evolve dynamically, progressively with the conversations, and thus represent evolving meta level Agent knowledge. We illustrate this theoretical model by a “teacher-student” dialogue experimentation, where an Agent learns a new performative at the completion of the conversation. Details of the implementation are not provided here, but are available.
Domains
Computer Science [cs]Origin | Files produced by the author(s) |
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