The paper presents the performance of a collision-free path planner designed for PLM application purposes. The algorithm principle is based on a iterative probabilistic diffusion principle [9]. The paper puts emphasis on efficiency and practicality analysis. It focuses on experiments dealing with disassembly problems as well as robot programming. Efficiency is evaluated in terms of computation ...

We present PCRISP, a sentence generation system for probabilistic TAG grammars which performs sentence planning and surface realization in an integrated fashion, in the style of the SPUD system. PCRISP operates by converting the generation problem into a metric planning problem and solving it using an offthe-shelf planner. We evaluate PCRISP on the WSJ corpus and identify trade-offs between cov...

Autonomous exploration requires robots to generate informative trajectories iteratively. Although sampling-based methods are highly efficient in unmanned aerial vehicle exploration, many of these do not effectively utilize the sampled information from previous planning iterations, leading redundant computation and longer time. Also, few have explicitly shown their ability dynamic environments e...

We show that Gul and Pesendorfer’s [Econometrica 69 (2001) 1403] representation result for preferences with temptation and self-control can be reexpressed in terms of a costly intrapersonal conflict between a Planner and Doer, as in Thaler and Shefrin [J. Political Econ. 89 (1981) 392] and psychologists’ standard view of self-control problems.  2002 Elsevier Science B.V. All rights reserved.

This paper presents some enhancements in the temporal reasoning of a Hierarchical Task Network (HTN) planner, named SIADEX, that, up to authors knowledge, no other HTN planner has. These new features include a sound partial order metric structure, deadlines, temporal landmarking or synchronization capabilities built on top of a Simple Temporal Network [3].

Probabilistic planners can have various planning objectives: usually they either maximize the probability of goal achievement or minimize the expected execution cost of the plan. Researchers have largely ignored the problem how to incorporate risk-sensitive attitudes into their planning mechanisms. We discuss a risk-sensitive planning approach that is based on utility theory. Our key result is ...

Many planning and scheduling applications require the ability to deal with uncertainty. Often this uncertainty can be characterized in terms of probability distributions on the initial conditions and on the outcomes of actions. These distributions can be used to guide a planner towards the most likely plan for achieving the goals. This work is focused on developing domain-independent heuristics...

This paper presents an optimal planner for the international probabilistic planning competition at ICAPS-08, IPPC-2008 for short. The planner solves non-deterministic action planning problems with binary decision diagrams. The efficiency of the planning approach is based on a translation of the non-deterministic planning problems into a twoplayer turn-taking game, with a set of actions selected...

The emerging area of intelligent unmanned aerial vehicle (UAV) research has shown rapid development in recent years and offers a great number of research challenges for artificial intelligence. For both military and civil applications, there is a desire to develop more sophisticated UAV platforms where the emphasis is placed on development of intelligent capabilities. Imagine a mission scenario...

In this paper, we present a framework for studying ligand binding which is based on techniques recently developed in the robotics motion planning community. We are interested in locating binding sites on the protein for a ligand molecule. Our work investigates the performance of a fully automated motion planner, as well as the effects of supplementary user input collected using a haptic device....