Recent literature in multiagent systems show a significant increase in interest and research on normative systems which are defined as (Boella, Torre, & Verhagen, 2008): A normative multiagent system is a multiagent system organized by means of mechanisms to represent, communicate, distribute, detect, create, modify, and enforce norms, and mechanisms to deliberate about norms and detect norm vi...

In this paper we present a multiagent system for landmark-based navigation in unknown environments. We propose a bidding mechanism to coordinate the actions requested by the different agents. The navigation system has been tested on a real robot on indoor unstructured environments.

This paper introduces some considerations about simulation practice and a schema of the models that are implicitly and explicitly involved in a Multi-Agent Based Simulation (MABS). The aim of this work is to set simulation inside scientific framework. In order to do that we give an interpretation of the levels that compound a simulation and that constitute different kinds of abstraction. A clea...

In this paper, we present an object-oriented framework for situated multiagent systems. The framework integrates various mechanisms for adaptivity we have developed and applied in our research, including selective perception, protocol-based communication, behavior-based decision making with roles and situated commitments, and laws that mediate the activities of agents in the environment. The fr...

This paper discusses issues related with learning resources brokerage systems. It introduces a marketbased modeling approach and proposes a virtual market model design of a brokerage system based on multi-agent analysis.

Introducing confidence in multi-agent systems gives agents a form of control in making decisions and helps to improve the decision making process in such systems. Consequently, modeling confidence of agents is important in heterogeneous agent communities. The inability to detect an agent’s confidence can be a reason for inaccurate decision. Several weaknesses have been found in current trust an...

This paper describes a multiagent variant of Dyna-Q called M-Dyna-Q. Dyna-Q is an integrated single-agent framework for planning, reacting, and learning. Like DynaQ, M-Dyna-Q employs two key ideas: learning results can serve as a valuable input for both planning and reacting, and results of planning and reacting can serve as a valuable input to learning. M-Dyna-Q extends Dyna-Q in that planning...

This paper focuses on a solution to the problem of task allocation through coalition formation and presents the design and implementation of a framework for this purpose. The framework serves as a multi-agent execution environment where worker agents follow the Shehory-Kraus’s coalition formation algorithm to negotiate and form coalitions. Worker agents prefer to form an optimal coalition to ma...

This paper aims at defining the semantics of Agent Communication Languages (ACLs) in terms of changes in the social relationships between agents, represented in terms of social commitments. We take commitment to be a primitive concept underlying the social dimension of multiagent systems, and define a basic artificial institution that provides agents with the means to affect the commitment netw...

We present a cooperative, multistep negotiation mechanism for multiagent systems. This mechanism uses marginal utility gain and marginal utility cost to structure the negotiation process. This enables an agent to understand another agent’s situation in order to find a solution that increases their combined utility. These two values summarize the agent’s local information and reduce the communic...