Towards Adaptive Programming Integrating Reinforcement Learning into a Programming Language

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Executive Summary

Current programming languages and software engineering paradigms are proving insufficient for building intelligent multi-agent systems - such as interactive games and narratives - where developers are called upon to write increasingly complex behavior for agents in dynamic environments. A promising solution is to build adaptive systems; that is, to develop software written specifically to adapt to its environment by changing its behavior in response to what it observes in the world. In this paper the authors describe a new programming language, An Adaptive Behavior Language (A2BL), that implements adaptive programming primitives to support partial programming, a paradigm in which a programmer need only specify the details of behavior known at code-writing time, leaving the run-time system to learn the rest.

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