CONTRIBUTIONS TO MULTI-AGENT SYSTEMS IMPLEMENTATION FOR PROJECT SCHEDULING

Increasing project complexity makes scheduling problems more difficult to solve and requires more versatile algorithms. Two different approaches for the project scheduling optimization could be considered: TCPSP (Time-Constrained Project Scheduling), and RCPSP (Resource-Constrained Project Scheduling). In this paper we study thepossibility to apply Multi-Agent Systems (MAS) for these scheduling problems regarding different fitness functions. Wesearch for strengths and weaknesses of MAS as a prerequisite study for a further implementation of the TCSP on a specific MAS platform.multi-agent systems, scheduling, project management, planning

Modelling process knowledge in architectural design: A case-based approach

The paper presents on-going research aimed at the understanding and support of process knowledge in architectural design, from early and not sufficiently defined, to satisfactorily-defined phases. Today, technical, planning, management and environmental issues have created a scenario of such complexity that traditionally efficient control tools (e.g. technical manuals) are inadequate and there is a demand for new, integrated instruments to handle the decision process underlying architectural design. We assume design as a recursive and incrementally specified intentional planning activity, involving goals, constraints and their relationships. The essence of architectural design is thus encapsulated in the continual recursive transformation of the initial model, in order to map the desired state onto the enacted one. On the basis of this concept of design we describe the model of an environment aimed at progressively representing the enlarging space of acquired knowledge, and at supporting the designer's central role in the management of complexity

On Being Responsible

Joint responsibility is a mental and behavioural state which captures and formalizes many of the intuitive underpinnings of collaborative problem solving. It defines the pre-conditions which must hold before such activity can commence, how individuals should behave (in their own problem solving and towards others) once such problem solving has begun and minimum conditions which group participants must satisfy

Situation awareness and ability in coalitions

This paper proposes a discussion on the formal links between the Situation Calculus and the semantics of interpreted systems as far as they relate to Higher-Level Information Fusion tasks. Among these tasks Situation Analysis require to be able to reason about the decision processes of coalitions. Indeed in higher levels of information fusion, one not only need to know that a certain proposition is true (or that it has a certain numerical measure attached), but rather needs to model the circumstances under which this validity holds as well as agents' properties and constraints. In a previous paper the authors have proposed to use the Interpreted System semantics as a potential candidate for the unification of all levels of information fusion. In the present work we show how the proposed framework allow to bind reasoning about courses of action and Situation Awareness. We propose in this paper a (1) model of coalition, (2) a model of ability in the situation calculus language and (3) a model of situation awareness in the interpreted systems semantics. Combining the advantages of both Situation Calculus and the Interpreted Systems semantics, we show how the Situation Calculus can be framed into the Interpreted Systems semantics. We illustrate on the example of RAP compilation in a coalition context, how ability and situation awareness interact and what benefit is gained. Finally, we conclude this study with a discussion on possible future works

Rational physical agent reasoning beyond logic

The paper addresses the problem of defining a theoretical physical agent framework that satisfies practical requirements of programmability by non-programmer engineers and at the same time permitting fast realtime operation of agents on digital computer networks. The objective of the new framework is to enable the satisfaction of performance requirements on autonomous vehicles and robots in space exploration, deep underwater exploration, defense reconnaissance, automated manufacturing and household automation

Prediction of intent in robotics and multi-agent systems.

Moving beyond the stimulus contained in observable agent behaviour, i.e. understanding the underlying intent of the observed agent is of immense interest in a variety of domains that involve collaborative and competitive scenarios, for example assistive robotics, computer games, robot-human interaction, decision support and intelligent tutoring. This review paper examines approaches for performing action recognition and prediction of intent from a multi-disciplinary perspective, in both single robot and multi-agent scenarios, and analyses the underlying challenges, focusing mainly on generative approaches