45367497
Resolving Social Dilemmas Using Genetic Algorithms: Initial Results
5317468
Strongly Typed Genetic Programming in Evolving Cooperation Strategies
A key concern in genetic programming GP is the size of the state space which must be searched for large and complex problem do mains One method to reduce the state space size is by using Strongly Typed Genetic Programming STGP We applied both GP and STGP to construct cooperation strate gies to be used by multiple predator agents to pursue and capture a prey agent on a grid world This domain has been extensively studied in Distributed Arti cial Intelligence DAI as an easy to describe but di cult to solve cooperation problem The evolved programs from our systems are competitive with manually derived greedy algorithms In particular the STGP paradigm evolved strategies in which the predators were able to achieve their goal without explicitly sens ing the location of other predators or com municating with other predators This is an improvement over previous research in this area The results of our experiments indicate that STGP is able to evolve programs that perform signi cantly better than GP evolved programs In addition the programs gener ated by STGP were easier to understand
13878075
Optimal sequencing of individually rational contracts
Multiagent researchers have worked on the problem of determining optimal contracts between self-interested agents. In particular, Sandholm et al. [1,8] have both theoretically and experimentally studied the necessity and usefulness of different contract types under the assumption of individually myopically rational contracting. We study a variant of sequential contracting where the goal is to maximize social welfare through a fixed-length sequence of individually rational contracts. The space of possible contract sequences is exponential. We compare a greedy deterministic heuristic with a stochastic genetic algorithm based approach for this optimal sequential contract selection problem. We focus on sub-additive domains where individually rational contracts are feasible with side payments. We show that the GA-based approach consistently outperforms the deterministic heuristic by generating larger social welfare.
11191590
On parallel integer sorting
We present an optimal algorithm for sortingn integers in the range [1,nc] (for any constantc) for the EREW PRAM model where the word length isnε, for any ε>0. Using this algorithm, the best known upper bound for integer sorting on the (O(logn) word length) EREW PRAM model is improved. In addition, a novel parallel range reduction algorithm which results in a near optimal randomized integer sorting algorthm is presented. For the case when the keys are uniformly distributed integers in an arbitrary range, we give an algorithm whose expected running time is optimal.
30243464
Planar Graph Blocking for External Searching
We present a new scheme for storing a planar graph in external memory so that any online path can be traversed in an I-O efficient way. Our storage scheme significantly improves the previous results for planar graphs with bounded face size. We also prove an upper bound on I-O efficiency of any storage scheme for well-shaped triangulated meshes. For these meshes, our storage scheme achieves optimal performance.
26714
Local Decision Procedures for Avoiding the Tragedy of Commons
The social sciences literature abound in problems of providing and maintaining a public good in a society composed of self-interested individuals [6]. Public goods are social benefits that can be accessed by individuals irrespective of their personal contributions. Such problems are also addressed in the domain of agent based systems [15]. In this paper we address the problem of the Tragedy of the Commons [9], a particularly common social dilemma that leads to inefficient usage of shared resources. We present a decision procedure following which rational agents can optimally use a shared resource using only local information. Our experimental results confirm that the tragedy of the commons is successfully avoided and the shared resource is utilized to its capacity when agents following our prescribed decision procedure.
6559774
A Movie Recommendation System – An Application of Voting Theory in User Modeling
Our research agenda focuses on building software agents that can employ user modeling techniques to facilitate information access and management tasks. Personal assistant agents embody a clearly beneficial application of intelligent agent technology. A particular kind of assistant agents, recommender systems, can be used to recommend items of interest to users. To be successful, such systems should be able to model and reason with user preferences for items in the application domain. Our primary concern is to develop a reasoning procedure that can meaningfully and systematically tradeoff between user preferences. We have adapted mechanisms from voting theory that have desirable guarantees regarding the recommendations generated from stored preferences. To demonstrate the applicability of our technique, we have developed a movie recommender system that caters to the interests of users. We present issues and initial results based on experimental data of our research that employs voting theory for user modeling, focusing on issues that are especially important in the context of user modeling. We provide multiple query modalities by which the user can pose unconstrained, constrained, or instance-based queries. Our interactive agent learns a user model by gaining feedback aboutits recommended movies from the user. We also provide pro-active information gathering to make user interaction more rewarding. In the paper, we outline the current status of our implementation with particular emphasis on the mechanisms used to provide robust and effective recommendations.
158365
Long-distance 802.11b links: performance measurements and experience
The use of 802.11 long-distance links is a cost-effective means of providing wireless connectivity to rural areas. Although deployments in this setting are increasing, a systematic study of the performance of 802.11 in these settings is lacking. The contributions of this paper are two-fold: (a)we present a detailed performance study of a set of long-distance 802.11b links at various layers of the network stack, and (b)we document the various non-obvious experiences during our study.Our study includes eight long-distance links, ranging from 1km to 37km in length. Unlike prior studies of outdoor 802.11 links, we find that the error rate as a function of the received signal strength behaves close to theory. Time correlation of any packet errors is negligible across a range of time-scales. We have observed at least one of the link to be robust to rain and fog. But any interference on the long-distance links can be detrimental to performance. Apart from this however, such long-distance links can be planned to work well with predictable performance. During our measurements, we have observed a few hardware/driver quirks as well as system bottlenecks apart from the wireless link itself. We believe that our measurements and the documentation of our experience will help future network planning as well as protocol design for these networks.