405 research outputs found
Incremental planning to control a blackboard-based problem solver
To control problem solving activity, a planner must resolve uncertainty about which specific long-term goals (solutions) to pursue and about which sequences of actions will best achieve those goals. A planner is described that abstracts the problem solving state to recognize possible competing and compatible solutions and to roughly predict the importance and expense of developing these solutions. With this information, the planner plans sequences of problem solving activities that most efficiently resolve its uncertainty about which of the possible solutions to work toward. The planner only details actions for the near future because the results of these actions will influence how (and whether) a plan should be pursued. As problem solving proceeds, the planner adds new details to the plan incrementally, and monitors and repairs the plan to insure it achieves its goals whenever possible. Through experiments, researchers illustrate how these new mechanisms significantly improve problem solving decisions and reduce overall computation. They briefly discuss current research directions, including how these mechanisms can improve a problem solver's real-time response and can enhance cooperation in a distributed problem solving network
Resource Allocation Among Agents with MDP-Induced Preferences
Allocating scarce resources among agents to maximize global utility is, in
general, computationally challenging. We focus on problems where resources
enable agents to execute actions in stochastic environments, modeled as Markov
decision processes (MDPs), such that the value of a resource bundle is defined
as the expected value of the optimal MDP policy realizable given these
resources. We present an algorithm that simultaneously solves the
resource-allocation and the policy-optimization problems. This allows us to
avoid explicitly representing utilities over exponentially many resource
bundles, leading to drastic (often exponential) reductions in computational
complexity. We then use this algorithm in the context of self-interested agents
to design a combinatorial auction for allocating resources. We empirically
demonstrate the effectiveness of our approach by showing that it can, in
minutes, optimally solve problems for which a straightforward combinatorial
resource-allocation technique would require the agents to enumerate up to 2^100
resource bundles and the auctioneer to solve an NP-complete problem with an
input of that size
Security Attributes Based Digital Rights Management
Most real-life systems delegate responsibilities to different authorities. We apply this model to a digital rights management system, to achieve flexible security. In our model a hierarchy of authorities issues certificates that are linked by cryptographic means. This linkage establishes a chain of control, identity-attribute-rights, and allows flexible rights control over content. Typical security objectives, such as identification, authentication, authorization and access control can be realised. Content keys are personalised to detect illegal super distribution. We describe a working prototype, which we develop using standard techniques, such as standard certificates, XML and Java. We present experimental results to evaluate the scalability of the system. A formal analysis demonstrates that our design is able to detect a form of illegal super distribution
Use of Markov Chains to Design an Agent Bidding Strategy for Continuous Double Auctions
As computational agents are developed for increasingly complicated e-commerce
applications, the complexity of the decisions they face demands advances in
artificial intelligence techniques. For example, an agent representing a seller
in an auction should try to maximize the seller's profit by reasoning about a
variety of possibly uncertain pieces of information, such as the maximum prices
various buyers might be willing to pay, the possible prices being offered by
competing sellers, the rules by which the auction operates, the dynamic arrival
and matching of offers to buy and sell, and so on. A naive application of
multiagent reasoning techniques would require the seller's agent to explicitly
model all of the other agents through an extended time horizon, rendering the
problem intractable for many realistically-sized problems. We have instead
devised a new strategy that an agent can use to determine its bid price based
on a more tractable Markov chain model of the auction process. We have
experimentally identified the conditions under which our new strategy works
well, as well as how well it works in comparison to the optimal performance the
agent could have achieved had it known the future. Our results show that our
new strategy in general performs well, outperforming other tractable heuristic
strategies in a majority of experiments, and is particularly effective in a
'seller?s market', where many buy offers are available
Defect and Hodge numbers of hypersurfaces
We define defect for hypersurfaces with A-D-E singularities in complex
projective normal Cohen-Macaulay fourfolds having some vanishing properties of
Bott-type and prove formulae for Hodge numbers of big resolutions of such
hypersurfaces. We compute Hodge numbers of Calabi-Yau manifolds obtained as
small resolutions of cuspidal triple sextics and double octics with higher A_j
singularities.Comment: 25 page
Chen-Ruan cohomology of ADE singularities
We study Ruan's \textit{cohomological crepant resolution conjecture} for
orbifolds with transversal ADE singularities. In the -case we compute both
the Chen-Ruan cohomology ring and the quantum corrected
cohomology ring . The former is achieved in general, the
later up to some additional, technical assumptions. We construct an explicit
isomorphism between and in the -case,
verifying Ruan's conjecture. In the -case, the family
is not defined for . This implies that
the conjecture should be slightly modified. We propose a new conjecture in the
-case which we prove in the -case by constructing an explicit
isomorphism.Comment: This is a short version of my Ph.D. Thesis math.AG/0510528. Version
2: chapters 2,3,4 and 5 has been rewritten using the language of groupoids; a
link with the classical McKay correpondence is given. International Journal
of Mathematics (to appear
Book Reviews
Cases on Quasi Contract, by Edward S. Thurston. American Case Book Series. St. Paul: West Publishing Co., I916; pp. 622
Search reduction in hierarchical distributed problem solving
Knoblock and Korf have determined that abstraction can reduce search at a single agent from exponential to linear complexity (Knoblock 1991; Korf 1987). We extend their results by showing how concurrent problem solving among multiple agents using abstraction can further reduce search to logarithmic complexity. We empirically validate our formal analysis by showing that it correctly predicts performance for the Towers of Hanoi problem (which meets all of the assumptions of the analysis). Furthermore, a powerful form of abstraction for large multiagent systems is to group agents into teams, and teams of agents into larger teams, to form an organizational pyramid. We apply our analysis to such an organization of agents and demonstrate the results in a delivery task domain. Our predictions about abstraction's benefits can also be met in this more realistic domain, even though assumptions made in our analysis are violated. Our analytical results thus hold the promise for explaining in general terms many experimental observations made in specific distributed AI systems, and we demonstrate this ability with examples from prior research.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/42828/1/10726_2005_Article_BF01384251.pd
Atom Interferometers
Interference with atomic and molecular matter waves is a rich branch of
atomic physics and quantum optics. It started with atom diffraction from
crystal surfaces and the separated oscillatory fields technique used in atomic
clocks. Atom interferometry is now reaching maturity as a powerful art with
many applications in modern science. In this review we first describe the basic
tools for coherent atom optics including diffraction by nanostructures and
laser light, three-grating interferometers, and double wells on AtomChips. Then
we review scientific advances in a broad range of fields that have resulted
from the application of atom interferometers. These are grouped in three
categories: (1) fundamental quantum science, (2) precision metrology and (3)
atomic and molecular physics. Although some experiments with Bose Einstein
condensates are included, the focus of the review is on linear matter wave
optics, i.e. phenomena where each single atom interferes with itself.Comment: submitted to Reviews of Modern Physic
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