AIPLNov 12, 2019

Aplib: Tactical Programming of Intelligent Agents

arXiv:1911.04710v12 citations
Originality Incremental advance
AI Analysis

It provides a tool for developers to program intelligent agents more effectively by integrating tactical programming into Java, though it is incremental as it builds on existing BDI frameworks.

The paper introduces aplib, a Java library for programming intelligent agents that combines BDI and multi-agency with a novel tactical programming layer inspired by theorem proving, offering the fluency of a Domain Specific Language while leveraging Java's ecosystem.

This paper presents aplib, a Java library for programming intelligent agents, featuring BDI and multi agency, but adding on top of it a novel layer of tactical programming inspired by the domain of theorem proving. Aplib is also implemented in such a way to provide the fluency of a Domain Specific Language (DSL). Compared to dedicated BDI agent programming languages such as JASON, 2APL, or GOAL,aplib's embedded DSL approach does mean that \aplib\ programmers will still be limited by Java syntax, but on other hand they get all the advantages that Java programmers get: rich language features (object orientation, static type checking, $λ$-expression, libraries, etc), a whole array of development tools, integration with other technologies, large community, etc.

Code Implementations1 repo
Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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