Code patterns for agent-oriented programming

ABSTRACT

The mainstream approach to design of BDI-inspired agent programming languages is to choose a set of agent-oriented features with a particular semantics and their subsequent implementation in the programming language interpreter. The language designer's choices thus impose strong constraints on the architecture of the implemented agents as well as only a limited toolbox of high-level language constructs for encoding the agent program.

As an alternative, we propose a purely syntactic approach to designing an agent programming language. On the substrate of Behavioural State Machines (BSM ), a generic modular programming language for hybrid agents, we show how an agent designer can implement high-level agent-oriented constructs in the form of code patterns (macros). To express the semantics of agent programs in the logic-agnostic programming language of BSM, we propose LTL program annotations and subsequently introduce DCTL*, an extension of the CTL* logic with features of dynamic logic, for reasoning about traces of BSM program executions. We show how DCTL* specifications can be used to prove relevant properties of code patterns. Moreover, DCTL* allows for natural verification of BSM agent programs.

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INDEX TERMS

Primary Classification:
  F. Theory of Computation
  F.3 LOGICS AND MEANINGS OF PROGRAMS
      F.3.2 Semantics of Programming Languages

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
        I.2.11 Distributed Artificial Intelligence
            Subjects: Intelligent agents
      I.2.5 Programming Languages and Software

Keywords:
agent-oriented programming, ai, code patterns, description level: methodologies and languages, focus: agent programming languages, inspiration source: robotics, temporal logic