A BDI agent programming language with failure handling, declarative goals, and planning

Agents are an important technology that have the potential to take over contemporary methods for analysing, designing, and implementing complex software. The Belief- Desire-Intention (BDI) agent paradigm has proven to be one of the major approaches to intelligent agent systems, both in academia and in industry. Typical BDI agent-oriented programming languages rely on user-provided ''plan libraries'' to achieve goals, and online context sensitive subgoal selection and expansion. These allow for the development of systems that are extremely flexible and responsive to the environment, and as a result, well suited for complex applications with (soft) real-time reasoning and control requirements. Nonetheless, complex decision making that goes beyond, but is compatible with, run-time context-dependent plan selection is one of the most natural and important next steps within this technology. In this paper we develop a typical BDI-style agent-oriented programming language that enhances usual BDI programming style with three distinguished features: declarative goals, look-ahead planning, and failure handling. First, an account that mixes both procedural and declarative aspects of goals is necessary in order to reason about important properties of goals and to decouple plans from what these plans are meant to achieve. Second, lookahead deliberation about the effects of one choice of expansion over another is clearly desirable or even mandatory in many circumstances so as to guarantee goal achievability and to avoid undesired situations. Finally, a failure handling mechanism, suitably integrated with both declarative goals and planning, is required in order to model an adequate level of commitment to goals, as well as to be consistent with most real BDI implemented systems

Pitfalls of Agent-Oriented Development

While the theoretical and experimental foundations of agent-based systems are becoming increasingly well understood, comparatively little effort has been devoted to understanding the pragmatics of (multi-) agent systems development - the everyday reality of carrying out an agent-based development project. As a result, agent system developers are needlessly repeating the same mistakes, with the result that, at best, resources are wasted - at worst, projects fail. This paper identifies the main pitfalls that await the agent system developer, and where possible, makes tentative recommendations for how these pitfalls can be avoided or rectified

Are you a Good Employee or Simply a Good Guy? Infl?uence Costs and Contract Design.

We develop a principal-agent model with a moral hazard problem in which the principal has access to a hard signal (the level of output) and a soft signal (the supervision signal) about the agent?s level of effort. We show that the agent?'s ability to manipulate the soft signal increases the cost of implementing the effcient equilibrium, leading to wage compression when the infl?uence cost is privately incurred by the agent. When manipulation activities negatively affect the agent?s productivity through the level of output, the design of infl?uence-free contracts that deter manipulation may lead to high-powered incentives. This result implies that high-productivity workers face incentive schemes that are more sensitive to hard evidence than those faced by their low-productivity counterparts. In that context, the principal will tolerate infl?uence for low-productivity workers but not for high-productivity workers. We also fi?nd that in the case of productivity-based costs, it may be optimal for the principal not to supervise the agent, even if supervision is costless.principal-agent model with supervision, contract design, in?uence activities, manipulation, productivity-based influence costs, power of incentives

Implementing an Agent Trade Server

An experimental server for stock trading autonomous agents is presented and made available, together with an agent shell for swift development. The server, written in Java, was implemented as proof-of-concept for an agent trade server for a real financial exchange.Comment: 14 pages, 7 figures, intended for B/W printin