In coalition formation with self-interested agents both social welfare of the multi-agent system and stability of individual coalitions must be taken into account. However, in large-scale systems with thousands of agents, finding an optimal solution with respect to both metrics is infeasible.

Coalition formation, a key factor in multi-agent cooperation, can be solved optimally for at most a few dozen agents. This paper proposes a general approach to find suboptimal solutions for a large-scale coalition formation problem containing thousands of agents using multi-agent simulation. We model coalition formation as an iterative process in which agents join and leave coalitions, and we propose several valuation functions that assign values to the coalitions. We propose several coalition selection strategies that agents may use to decide whether or not to leave their current coalition and which coalition to join. We also show how these valuation functions and coalition selection strategies represent specific coalition formation applications. Finally, we show almost-optimal performance of our algorithms in small-scale scenarios by comparing our solutions with an optimal solution, and we show stable performance in a large-scale setting in which searching for the optimal solution is not feasible.

An autonomic system is a system capable of managing itself and adjusting its actions in the face of environmental changes. Autonomic systems are currently developed using ad-hoc approaches, which do not promote repeatable successes. In this paper, we

It has been said that the only constant in life is change. This rule can also be directly applied to the lives of organizations. Any organization of non-trivial size, scope, life expectancy or function, is destined to change. An organization without

In harsh or dangerous environments, robots can lose function in multiple sensors and effectors over the mission, thus reducing their overall capability. If the capabilities provided by these sensors/effectors are necessary for mission completion, having an adaptive system that can overcome these losses is critical to mission accomplishment. In this paper, we propose a solution using multiple agents, organized as a team, to give robots the ability to adapt and overcome sensor/effector loss. When a sensor/effector is lost, the team can reorganize to provide the robot highest operational utility, given its current capabilities. The robot can adapt to such losses by substituting other sets of sensors/effectors to provide the best overall capability. While the robot may operate at a lower level of effectiveness, it will be able continue its mission, if possible.

This paper reports our progress in applying multiagent systems analysis and design in the area of cooperative robotics. In this paper, we apply the Multiagent Systems Engineering (MaSE) methodology to design a team of autonomous, heterogeneous search and rescue robots. MaSE provides a top-down approach to building cooperative robotic systems instead of the bottom-up approach employed in most robotic implementations. We follow the MaSE steps and discuss various approaches and their impact on the final system design.

This paper describes the Multiagent Systems Engineering (MaSE) methodology. MaSE is a general purpose, methodology for developing heterogeneous multiagent systems. MaSE uses a number of graphically based models to describe system goals, behaviors, agent types, and agent communication interfaces. MaSE also provides a way to specify architecture-independent detailed definition of the internal agent design. An example of applying the MaSE methodology is also presented.

Formal software specification has long been touted as a way to increase the quality and reliability of software; however, it remains an intricate, manually intensive activity. An alternative to using formal specifications directly is to translate graphically based, semiformal specifications into formal specifications. However, before this translation can take place, a formal definition of basic object oriented concepts must be found. The paper presents an algebraic model of object orientation that defines how object oriented concepts can be represented algebraically using an object oriented algebraic specification language O-SLANG. O-SLANG combines basic algebraic specification constructs with category theory operations to capture internal object class structure, as well as relationships between classes.