Perceptron predictor is well known as its ability to exploit long history information. A limitation of perceptron predictor is that it cannot effectively predict linearly inseparable correlations. In this paper, we present a revised perceptron predictor with separated Taken/Not-Taken weight tables (SWP). It can treat the taken/not taken correlation separately and therefore predict some linearly...

In this work we describe a protocol by which two of three parties generate two bipartite entangled state among themselves without involving third party, from a non maximal W state or W type state |X〉 = α|001〉123+β|010〉123+γ|100〉123, α+ β+γ = 1 shared by three distant partners. Also we have considered the case β = γ, to obtain a range for α, for which the local output states are separable and no...

The paper presents a method to control random sampling in motion planning algorithms. The principle of the method is to use on line the results of a probabilistic planner to describe the free space in which the planning takes place, by computing a Principal Component Analysis (PCA). This method identifies the locally free directions of the free space. Given that description, our algorithm accel...

We consider the problem of planning in domains with continuous linear numeric change. Such change cannot always be adequately modelled by discretisation and is a key facet of many interesting problems. We show how a forward-chaining temporal planner can be extended to reason with actions with continuous linear effects. We extend a temporal planner to handle numeric values using linear programmi...

We present an approach to linear logic planning where an explicit correspondence between partial order plans and multiplicative exponential linear logic proofs is established. This is performed by extracting partial order plans from sound and complete encodings of planning problems in multiplicative exponential linear logic in a way that exhibits a non-interleaving behavioral concurrency semant...

Sensor planning is concerned with when to sense and what to sense We study sensor planning in the context of planning objectives that trade o between minimizing the worst case expected and best case plan execution costs Sensor planning with these planning objectives is interesting because they are realistic and the frequency of sensing changes with the plan ning objective more pessimistic decis...

Many recent planning heuristics are based on LP optimization. However, planning experts mostly use LP solvers as a black box and it is often not obvious to them which LP techniques would be most suitable for their specific applications. To foster the communication between the planning and the optimization community, this paper gives an easily accessible overview over these recent LP-based heuri...

The “planning as satisfiability” approach for classical planning establishes a correspondence between planning problems and logical theories, and, consequently, between plans and models. This work proposes a similar framework for contingency planning: considering contingent planning problems where the sources of indeterminism are incomplete knowledge about the initial state, non-inertial fluent...

We present an approach to linear logic planning where an explicit correspondence between partial order plans and multiplicative exponential linear logic proofs is established. This is performed by extracting partial order plans from sound and complete encodings of planning problems in multiplicative exponential linear logic in a way that exhibits a non-interleaving behavioral concurrency semant...