Most autonomous agents are situated in a social context and need to interact with other agents (both human and artificial) to complete their problem solving objectives. Such agents are usually capable of performing a wide range of actions and engaging in a variety of social interactions. Faced with this variety of options, an agent must decide what to do. There are many potential decision making functions which could be employed to make the choice. Each such function will have a different effect on the success of the individual agent and of the overall system in which it is situated. Therefore, this paper examines agents' decision making functions to ascertain their likely properties and attributes. A framework for characterising social decision making is presented and a socially responsible decision making principle is proposed which enables both the agent and the overall system to perform well. This principle is illustrated, and empirically evaluated, in a multiagent system for unloading lorries at a warehouse. 1.

Systems composed of multiple interacting problem solvers are becoming increasingly pervasive and have been championed in some quarters as the basis of the next generation of intelligent information systems. If this technology is to fulfill its true potential then it is important that the systems which are developed have a sound theoretical grounding. One aspect of this foundation, namely the model of collaborative problem solving, is examined in this paper. A synergistic review of existing models of cooperation is presented, their weaknesses are highlighted and a new model (called joint responsibility) is introduced. Joint responsibility is then used to specify a novel high-level agent architecture for cooperative problem solving in which the mentalistic notions of belief, desire, intention and joint intention play a central role in guiding an individual's and the group's problem solving behaviour. An implementation of this highlevel architecture is then discussed and its utility is il...

Because we think that plans or strategies are useful for coordinating multiple agents, and because we hypothesize that most of the plans we use are build partly by us and partly by our immediate environment (which includes other agents), this paper is devoted to the conditions in which strategies can be viewed as the result of interactions between simple agents, each of them having only local information about the state of the world. Our approach is based on the study of some examples of reactive agents applications. Their features arebriefly described and we underline, in each of them, what we call the emergent strategies obtained from the local interactions between the agents. Three examples are studied this way: the eco-problem-solving implementations of Pengi and the N-Puzzle, and the sociogenesis process occuring in the artificial ant colonies that compose the MANTA project. We then consider a typical strategical game (chess), and see how to decompose it through a distributed reac...

We present in this paper a distributed approach for solving the N-puzzle. This approach is based on the decomposition of a problem into the set of the smallest independent subgoals that can be described, be they serializable or not. These subgoals are at their turn decomposed into agents whose task is to satisfy the subgoal. We have chosen the Eco-Problem-Solving model for describing the internal functioning of these agents. Each of them is then characterized by a state, a goal, a satisfaction behavior and a flight behavior. Those kernel behaviors invoke domaindependent actions that must fit with the domain in which the agent is involved. The description of these actions is made by presenting their basic algorithm and the heuristics used in it, namely the MGB and VMGB distance computations. A simple example of solving is presented, followed by an example of what can be called an "emergent solution" to the problem of the corners. We prove, then, that the method is complete and decidabl...

Abstract 2 Most autonomous agents are situated in a social context and need to interact with other agents (both human and artificial) to complete their problem solving objectives. Such agents are usually capable of performing a wide range of actions and engaging in a variety of social interactions. Faced with this variety of options, an agent must decide what to do. There are many potential decision making functions that could be employed to make the choice. Each such function will have a different effect on the success of the individual agent and of the overall system in which it is situated. To this end, this thesis examines agents ’ decision making functions to ascertain their likely properties and attributes. A novel framework for characterising social decision making is presented which provides explicit reasoning about the potential benefits of the individual agent, particular sub-groups of agents or the overall system. This framework enables multi-farious social interaction attitudes to be identified and defined; ranging from the purely self-interested to the purely altruistic. In particular, however, the focus is on the spectrum of socially responsible agent behaviours in which agents attempt to balance their own needs with those of the overall system. Such behaviour aims to ensure that both the agent and the overall system perform well.

The paper presents a Multi Agent Systems (MAS) approach to crowd modelling, based on the Situated Cellular Agents (SCA) model. This is a special class of Multilayered Multi Agent Situated System (MMASS), rooted on Cellular Automata, providing an explicit spatial representation and the definition of adjacency geometries. The model also defines a concept of autonomous agent, provided with an internal architecture and individual state and behaviour, capable of different means of space--mediated interaction (synchronous, between adjacent agents, and asynchronous among distant entities). Heterogenous entities may be modelled through the specification of different agent types, defining different behaviours and perceptive capabilities. After a brief description of the model, its application to simple crowd behaviours will be given (e.g. lane and group formation), and an application providing the integration of a bidimensional simulator based on this model and a 3D modelling application (3D Studio) will also be described. The adoption of this kind of system allows to specify, simulate and evaluate a design solution, but also to easily produce a realistic visualization of the simulation, in order to facilitate the communication with involved actors. In fact, while expert decision-- makers often require only abstract and analytical results deriving from the simulation, other people involved in the decision--making process related to the design may be helped by other forms of graphical representation.

Abstract. Ubiquitous workspaces are technology and media rich environments that support intense collaborative activities through the application of ubiquitous computing, artificial intelligence, and advanced human interaction approaches. These environments are highly interactive and intelligent spaces created through the augmentation of physical workspaces, such as meeting rooms, with a range of display technologies, personal information appliances, speech and natural language interfaces, and contextual sensors. A key focus of our work relates to the effective application of these types of workspaces in enterprise settings. In particular, we are investigating how these future workspaces, or LiveSpaces, can be used to support multiple synchronised teams engaged in military planning within future headquarters environments. This paper discusses the use of workspace simulation to support our investigations into the use of these augmented synchronised planning spaces. 1.

Summary: The challenges in today’s global economy are flexibility and fast reactions to customer requests. To cope with these requirements there is a need for intelligent adaptive planning and control systems. The multiagent approach offers favorable prospects for adequate solutions. A simulation platform for the development of multiagent systems in logistics is presented. Logistics is viewed as socio-technical which enables to take into account human resources within the design process explicitly according their importance. This simulation platform is based on the discrete-event simulation environment HIDES developed at our institute. The modeling bases of the simulation is a reference model of logistics comprising few specific basic elements to be used according to a well-defined syntactical structure. To realize multiagent systems a particular management level is added, where the agents and the interfaces to human resources are located. The platform is intended to provide a substantial support for developing multiagent systems.