In this paper, various properties of particular type of Hamiltonian graph and it's edge-disjoint Hamiltonian circuits have been discussed. It has been found that the intersection graph obtained from Euler Diagram is not Hamiltonian. The graph H(3m + 7, 6m + 14) for m ? 1, which is planner, regular of degree four, non-bipartite but Hamiltonian graph , has perfect matching 4 with nonrepeated...

We describe Probapop, a partial-order probabilistic planning system. Probapop is a blind (conformant) planner that finds plans for domains involving probabilistic actions but no observability. The Probapop implementation is based on Vhpop, a partial-order deterministic planner written in C++. The Probapop algorithm uses plan graph based heuristics for selecting a plan from the search queue, and...

In this paper we describe a motion planner for a mobile robot on a natural terrain. This planner takes into account placement constraints of the robot on the terrain and landmark visibility. It is based on a two-step approach: during the rst step, a global graph of subgoals is generated in order to guide the robot through the landmark visibility regions; the second step consists in planning loc...

Motion planning refers to the ability of a system to automatically plan its motions. It is considered central to the development of autonomous robots. In the last decade, much research effort was done on the application of probabilistic roadmaps methods (PRM) for different types of problems (Kavraki et al., 1996; Svestka & Overmars, 1997; Bohlin & Kavraki, 2000; Sánchez & Latombe, 2002). There ...

In this paper we present a planner, LPRPG-P, capable of reasoning with the non-temporal subset of PDDL3 preferences. Our focus is on computation of relaxed plan based heuristics that effectively guide a planner towards good solutions satisfying preferences. We build on the planner LPRPG, a hybrid relaxed planning graph (RPG)–linear programming (LP) approach. We make extensions to the RPG to rea...

Some recent works in conditional planning have proposed reachability heuristics to improve planner scalability, but many lack a formal description of the properties of their distance estimates. To place previous work in context and extend work on heuristics for conditional planning, we provide a formal basis for distance estimates between belief states. We give a definition for the distance bet...

Most recent strides in scaling up planning have centered around two competing themes–disjunctive planners, exemplified by Graphplan, and heuristic state search planners, exemplified by HSP and HSPR. In this paper, we describe a planner called AltAlt, which successfully combines the advantages of the two competing paradigms to develop a planner that is significantly more powerful than either of ...

In the last decade three main ideas have revolutionized the Artificial Intelligence (AI) planning methods: the plan graph search structure, planning as satisfiability and the search guided by a heuristic function calculated from a relaxed plan. In this paper we present a new planner, named HPP (Heuristic Progressive Planner), that has been implemented using several ideas extracted from other he...

Planning for and controlling a network of interacting devices requires a planner that accounts for the automatic timed transitions of devices, while meeting deadlines and achieving durative goals. Consider a planner for an imaging satellite with a camera that cannot tolerate exhaust. The planner would need to determine that opening a valve causes a chain reaction that ignites the engine, and th...