1281859
Unsupervised Surrogate Agents and Search Bias Change in Flexible Distributed Scheduling
Computational infrastructures for cooperative work should contain embedded agents for handling many routine tasks (Galegher, Kraut, Egldo 1990), but as the number of agents increases and the agents become geographically and/or conceptually dispersed, supervision of the agents will become increasingly problematic. We argue that agents should be provided with deep domain knowledge that allows them to make justifiable decisions, rather than shallow models of users to mimic. In this paper, we use the application domain of distributed meeting scheduling to investigate how agents embodying deeper domain knowledge can choose among alternative strategies for searching their calendars in order to create flexible schedules within reasonable cost.
482217
Believing others: pro and cons
Under the assumption that agents remain in the system for significant time periods, or that the agent composition changes only slowly Sen (1996) has previously presented a prescriptive strategy for promoting and sustaining cooperation among self-interested agents. The adaptive, probabilistic policy prescribed promotes reciprocative cooperation that improves both individual and group performance in the long run. In the short run, however, selfish agents could still exploit reciprocative agents. In this paper we evaluate the hypothesis that the exploitative tendencies of selfish agents can be effectively curbed if reciprocative agents share their "opinions" of other agents. Since the true nature of agents are not known a priori and is learned from experience, believing others can also pose other hazards. We provide a learned trust-based evaluation function that is shown to resist both individual and concerted deception on the part of selfish agents.
10373451
Reciprocal resource sharing in P2P environments
Peer-to-peer (P2P) systems enable users to share resources in a networked environment without worrying about issues such as scalability and load balancing. Unlike exchange of goods in a traditional market, resource exchange in P2P networks does not involve monetary transactions. This makes P2P systems vulnerable to problems including the free-rider problem that enables users to acquire resources without contributing anything, collusion between groups of users to incorrectly promote or malign other users, and zero-cost identity that enables nodes to obliterate unfavorable history without incurring any expenditure. Previous research addresses these issues using user-reputation, referrals, and shared history based techniques. Here, we describe a multi-agent based reciprocity mechanism where each user's agent makes the decision to share a resource with a requesting user based on the amount of resources previously provided by the requesting user to the providing user and globally in the system. A robust reputation mechanism is proposed to avoid the differential exploitations by the free-riders and to prevent collusion. Experimental results on a simulated P2P network addresses the problems identified above and shows that users adopting the reciprocative mechanism outperform users that do not share resources in the P2P network. Hence, our proposed reciprocative mechanism effectively suppresses free-riding.
12119095
Correlating Internal Parameters and External Performance: Learning Soccer Agents
We have developed a Soccer simulator in Java, which allows us to evaluate agent behavioral strategies for effectively collaborating with other team members while countering threats posed by the opposing team. Whereas action selection mechanisms to decide when to shoot, pass, dribble, guard opponent, tackle, etc. are important from a player's viewpoint, learning the capabilities of individual opponents from repeated encounters can provide critical information for the success of a team. Each agent is described by a set of skill levels for different soccer skills. A soccer agent uses its incomplete perceptions, model of the changing environment, knowledge of the skill levels of its own team players, and estimated skill levels of the opponent team players to select the most prudent action. In this paper, we identify learning opportunities for soccer agents, and investigate some of these possibilities in detail. Initial experimental results demonstrate the advantage of learning agents.
43158386
Evolution and learning in multiagent systems
1062630
The Role of Commitment in Cooperative Negotiation
Cooperative information agents need mechanisms that enable them to work together effectively while solving common problems. We investigate the use of commitment by agents to proposed actions as a mechanism that allow agents to work concurrently on interdependent problems. Judicious use of commitment can not only increase the throughput of cooperative information systems, but also allow them to deal flexibly with dynamically changing environments. We use the domain of distributed scheduling to demonstrate that static commitment strategies are ineffective. Results from simulated experiments are used to identify the environmental features on which an adaptive commitment strategy should be predicated.
16079000
Searching for optimal coalition structures
Coalition formation has been a very active area of research in multiagent systems. Most of this research has concentrated on decentralized procedures that allow self-interested agents to negotiate the formation of coalitions and division of coalition payoffs. A different line of research has addressed the problem of finding the optimal division of agents into coalitions such that the sum total of the the payoffs to all the coalitions is maximized (Larson and Sandholm, 1999). This is the optimal coalition structure identification problem. Deterministic search algorithms have been proposed and evaluated under the assumption that the performance of a coalition is independent of other coalitions. We use an order-based genetic algorithm (OBGA) as a stochastic search process to identify the optimal coalition structure. We compare the performance of the OBGA with a representative deterministic algorithm presented in the literature. Though the OBGA has no performance guarantees, it is found to dominate the deterministic algorithm in a significant number of problem settings. An additional advantage of the OBGA is its scalability to larger problem sizes and to problems where performance of a coalition depends on other coalitions in the environment.
2225573
Integrated scheduling of multimedia and hard real-time tasks
An integrated platform which is capable of meeting the requirements of both traditional real-time control processing and multimedia processing has enormous potential for accommodating various kinds of new applications. However, except for the simplest of situations, few, if any, research or commercial systems successfully provide architectural and OS mechanisms which can efficiently support both hard real-time computation and multimedia soft real-time computation. The authors propose a multimedia server execution on multiprocessor real-time operating systems to provide different classes of guarantee to support both types of processing. The multimedia server supports multiple periodic multimedia streams with a capability for graceful QoS degradation during system overload. They (i) develop several multimedia server scheduling algorithms, (ii) evaluate the performance of these algorithms, and (iii) discuss realistic system implementation issues on the SGI IRIX/REACT/PRO operating system.
17022940
Using Windows NT for Real-Time Applications: Experimental Observations and Recommendations
Windows NT was not designed as a real time operating system, but market forces and the acceptance of NT in industrial applications have generated a need for achieving real time functionality with NT. As its use for real time applications proliferates, based on an experimental evaluation of NT, we quantitatively characterize the obstacles placed by NT. As a result of these observations, we provide a set of recommendations for users to consider while building real time applications on NT. These are validated by the use of NT for a prototype application involving real time control that includes multimedia information processing. The results of the above study should provide system designers with guidelines, as well as insight, into the design of an architecture based on NT for supporting applications with components having real time constraints.
1068367
An Efficient Output-Size Sensitive Parallel Algorithm for Hidden-Surface Removal for Terrains
Abstract. We describe an efficient parallel algorithm for hidden-surface removal for terrain maps. The algorithm runs in O(log 4 n) steps on the CREW PRAM model with a work bound of O((n+k) \polylog ( n)) where n and k are the input and output sizes, respectively. In order to achieve the work bound we use a number of techniques, among which our use of persistent data structures is somewhat novel in the context of parallel algorithms.
781819
Dynamic point location in arrangements of hyperplanes
We present algorithms for maintaining data structures supporting fast (polylogarithmic) point-location and ray-shooting queries in arrangements of hyperplanes. This data structure allows for deletion and insertion of hyperplanes. Our algorithms use random bits in the construction of the data structure but do not make any assumptions about the update sequence or the hyperplanes in the input. The query bound for our data structure isO(polylog(n)), wheren is the number of hyperplanes at any given time, and theO notation indicates that the bound holds with high probability, where the probability is solely with respect to randomization in the data structure. By high probability we mean that the probability of error is inversely proportional to a large degree polynomial inn. The space requirement isO(nd). The cost of update isO(nd?1 logn. The expected cost of update isO(nd?1); the expectation is again solely with respect to randomization in the data structure. Our algorithm is extremely simple. 
 
We also give a related algorithm with optimalO(logn) query time, expectedO(nd) space requirement, and amortizedO(nd?1) expected cost of update. Moreover, our approach has a versatile quality which is likely to have further applications to other dynamic algorithms. 
 
Ford=2, 3 we also show how to obtain polylogarithmic update time in the CRCW PRAM model so that the processor-time product matches (within a polylogarithmic factor) the sequential update time.