A cooperation of agents in competitive environments is more complicated than in collaborative ones. Both the replanning and reconfiguration play the crucial role in the cooperation and introduce a means for an implementation of a system flexibility. The concepts of commitments, decommitments with the penalties and subcontractions may facilitate e#ective reconfiguration and replanning.

In this paper we aim to formally model individual, social and collective motivational attitudes in teams of agents involved in Cooperative Problem Solving. Particular attention is given to the strongest motivational attitude, collective commitment, which leads to team action. First, building on our previous work, a logical framework is sketched in which social commitments and collective intentions are formalized. Then, different versions of collective commitments are given, reflecting different aspects of Cooperative Problem Solving, and applicable in different situations. The definitions differ with respect to the aspects of teamwork of which the agents involved are aware, and the kind of awareness present within a team. In this way a kind of tuning mechanism is provided for the system developer to tune a version of collective commitment fitting the circumstances. Finally, we focus attention on a few exemplar versions of collective commitment resulting from instantiating the general tuning scheme, and sketch for which kinds of organization and application domains they are appropriate.

Abstract—We present an approach to plan representation in multi-actors scenarios that is suitable for flexible replanning and plan revision purposes. The key idea of the presented approach is in integration of (i) the results of an arbitrary HTN (hierarchical task network)-oriented planner with (ii) the concept of commitments, as a theoretically studied formalism representing mutual relations among intentions of collaborating agents. The paper presents formal model of recursive form of commitments and discusses how it can be deployed to a selected hierarchical planning scenario 1. I.

In some rescue or emergency situations, agents may act individually or on the basis of minimal coordination, while in others, fullfledged teamwork provides the only means for the rescue action to succeed. In such

Cooperative-problem-solving negotiations in competitive environments involve an initial conclusion of commitments as well as their possible adaptations during their execution. Conclusion of commitments, breaching the commitments (decommitments), their replanning and reconfiguration introduce means of achieving flexibility in cooperation among self-interested agents and require adequate negotiation means covering whole life cycle of the cooperation. We introduce Renegotiable Competitive Contract Net Protocol (RCCNP) enabling fully flexible contracting and cooperation in competitive environments. The protocol extends Competitive Contract Net Protocol (CCNP) by renegotiation phases, resolves a termination problem in the CCNP termination phase and keeping compliance to other FIPA standards it extends the set FIPA speech acts. Flexibility of commitments is achieved by employing leveled commitments. Renegotiation phases facilitate partial decommitments, extensions of commitments of currently committed parties and invitations of new parties into an already running cooperation. As RC-

Cooperation of agents in competitive environments is more complicated than in collaborative environments. Both replanning and reconfiguration play a crucial role in cooperation, and introduce a means for implementating a system flexibility. The concepts of commitments, decommitments with penalties and subcontracting may facilitate effective reconfiguration and replanning. Agents in competitive environments are fully autonomous and selfinterested. Therefore the setting of penalties and profit computation cannot be provided centrally. Both the costs and the gain differ from agent to agent with respect to contracts already agreed and resources load. This paper proposes an acquaintance model for contracting in competitive environments and introduces possibilities of reconfigurating in competitive environments as a means of decommitment optimization with respect to resources load and profit maximization. The presented algorithm for contract price setting does not use any centralized knowledge and provides results corresponding to a realistic environment. A simple customerprovider scenario proves this algorithm in competitive contracting.

Abstract. In natural language we often use graded concepts, reflecting different intensity degrees of certain features. Whenever such concepts appear in a given real-life context, they need to be appropriately expressed in its models. In this paper, we provide a framework which allows for extending the BGI model of agency by grading beliefs, goals and intentions. We concentrate on TEAMLOG [6, 7, 8, 9, 12] and provide a complexity-optimal decision method for its graded version TEAMLOG K by translating it into CPDLreg (propositional dynamic logic with converse and “inclusion axioms ” characterized by regular languages). We also develop a tableau calculus which leads to the first EXPTIME (optimal) tableau decision procedure for CPDLreg. As CPDLreg is suitable for expressing complex properties of graded operators, the procedure can also be used as a decision tool for other multiagent formalisms.