This paper presents RepairSHOP a system capable of performing plan adaptation and plan repair. RepairSHOP is built on top of the HTN planner SHOP. RepairSHOP has three properties. The first property is its design modularity, which makes it is straightforward to apply the same process discussed

This paper presents a definition and framework for a novel type of adaptive data network: the cognitive network. In a cognitive network, the collection of elements that make up the network observes network conditions and then, using prior knowledge gained from previous interactions

This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility

task, but differ completely at the levels of synaptic strengths and single-unit responses. However, hierarchical clustering techniques applied to NETtalk reveal that these different networks have similar internal representations of letter-to-sound correspondences within groups of processing units

are necessary to establish a routing forwarding backbone. In ASCENT, each node assesses its connectivity and adapts its participation in the multihop network topology based on the measured operating region. This paper motivates and describes the ASCENT algorithm and presents analysis, simulation

and analysis; and to Gerrit Wolf for help in analytic planning. This report was prepared in connection with research supported by the Office of Naval Research (Organizational Effectiveness Research Program,, and by the Manpower Administration, U. S. Department of Labor . Since grantees conducting research

be accommodated by a fixed-resource system? Using a prediction task, a simple recurrent network (SRN) is trained on multiclausal sentences which contain multiply-embedded relative clauses. Principal component analysis of the hidden unit activation patterns reveals that the network solves the task by developing

Most practical work on AI planning systems during the last fteen years has been based on hierarchical task network (HTN) decomposition, but until now, there has been very little analytical work on the properties of HTN planners. This paper describes how the complexity of HTN planning varies

is first translated into an alternative representation called multivalued planning tasks, which makes many of the implicit constraints of a propositional planning task explicit. Exploiting this alternative representation, Fast Downward uses hierarchical decompositions of planning tasks for computing its

A Distributed Clustering Algorithm (DCA) and a Distributed Mobility-Adaptive Clustering (DMAC) algorithm are presented that partition the nodes of a fully mobile network (ad hoc network) into clusters, thus giving the network a hierarchical organization.