Meta-case-based reasoning: Self-improvement through self-understanding

Abstract

The ability to adapt is a key characteristic of intelligence. In this work we investigate model-based reasoning for enabling intelligent software agents to adapt themselves as their functional requirements change incrementally. We examine the use of reflection (an agent's knowledge and reasoning about itself) to accomplish adaptation (incremental revision of an agent's capabilities). Reflection in this work is enabled by a language called TMKL (Task-Method-Knowledge Language) which supports modelling of an agent's composition and teleology. A TMKL model of an agent explicitly represents the tasks the agent addresses, the methods it applies, and the knowledge it uses. These models are used in a reasoning shell called REM (Reflective Evolutionary Mind). REM enables the execution and incremental adaptation of agents that contain TMKL models of themselves.