The agent programming language meta-APL

Abstract. We describe a novel agent programming language, Meta-APL, and give its operational semantics. Meta-APL allows both agent programs and their associated deliberation strategy to be encoded in the same programming language. We define a notion of equivalence between programs written in different agent programming languages based on the notion of weak bisimulation equivalence. We show how to simulate (up to this notion of equivalence) programs written in other agent programming languages by programs of Meta-APL. This involves translating both the agent program and the deliberation strategy under which it is executed into Meta-APL.

Dynamic programming: An interactive approach

AbstractAn interactive approach to the formulation, modeling, analysis, and solution of discrete deterministic dynamic programming problems is presented. The approach utilizes APL both as the mathematical and the programming language. The interactive capabilities of APL and the simple one-to-one correspondence between the programming and the mathematical language provide an extremely convenient environment for dynamic programming investigations in general and for teaching/learning purposes in particular. The approach is illustrated by a simple model and a numerical example

Verifying heterogeneous multi-agent programs

We present a new approach to verifying heterogeneous multi-agent programs — multi-agent systems in which the agents are implemented in different (BDI-based) agent programming languages. Our approach is based on meta-APL, a BDI-based agent programming language that allows both an agent’s plans and its deliberation strategy to be encoded as part of the agent program. The agent programs comprising a heterogeneous multi-agent program are first translated into meta-APL, and the resulting system is then verified using the Maude term rewriting system. We prove correctness of translations of Jason and 3APL programs and deliberation strategies into meta-APL. Preliminary experimental results indicate that our approach can significantly out-perform previous approaches to verification of heterogeneous multi-agent programs

A MATHEMATICAL PROGRAMMING GENERATOR SYSTEM

This paper describes a mathematical programming generator that interprets problem statements written in the algebraic notation found in journal articles and text-books and outputs statements in the 'MPS formatâ used by IBMâs MPSX mathematical programming system. The system has been implemented in the APL programming language. Although originally designed for stand-alone use, it is currently being used as a component in an expert system that will help users formulate large linear programming models, The paper describes the syntax of the problem definition language and gives some illustrative examples. There are several unique features. First, the user can define objective function, constraint and right-hand-side coefficients as APL expressions. This leads to concise problem statements and also reduces data storage and processing requirements. Second, the system supports an integrated data base query language. Finally, there are a number of aids for model maintenance and sensitivity analysis. The last section of the paper describes the use of MPGEN in the expert system context.Information Systems Working Papers Serie

Meta-APL: a general language for agent programming

A key advantage of BDI-based agent programming is that agents can deliberate about which course of action to adopt to achieve a goal or respond to an event. However while state-of-the-art BDI-based agent programming languages provide flexible support for expressing plans, they are typically limited to a single, hard-coded, deliberation strategy(perhaps with some parameterisation) for all task environments. In this thesis, we describe a novel agent programming language, meta-APL, that allows both agent programs and the agent’s deliberation strategy to be encoded in the same programming language. Key steps in the execution cycle of meta-APL are reflected in the state of the agent and can be queried and updated by meta-APL rules, allowing a wide range of BDI deliberation strategies to be programmed. We give the syntax and the operational semantics of meta-APL, focussing on the connections between the agent’s state and its implementation. Finally, to illustrate the flexibility of meta-APL, we show how Jason and 3APL programs and deliberation strategy can be translated into meta-APL to give equivalent behaviour under weak bisimulation equivalence

Programming Deliberation Strategies in Meta-APL

A key advantage of BDI-based agent programming is that agents can deliberate about which course of action to adopt to achieve a goal or respond to an event. However, while state-of-the-art BDI-based agent programming languages provide flexible support for expressing plans, they are typically limited to a single, hard-coded, deliberation strategy (perhaps with some parameterisation) for all task environments. In this paper, we present an alternative approach. We show how both agent programs and the agent’s deliberation strategy can be encoded in the agent programming language meta-APL. Key steps in the execution cycle of meta-APL are reflected in the state of the agent and can be queried and updated by meta-APL rules, allowing BDI deliberation strategies to be programmed with ease. To illustrate the flexibility of meta-APL, we show how three typical BDI deliberation strategies can be programmed using meta-APL rules. We then show how meta-APL can used to program a novel adaptive deliberation strategy that avoids interference between intentions