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Deductive planning treats planning as a reasoning process within a formal logic. Several formal logics have been applied in various deductive planning systems, but none is completely satisfactory and widely accepted by planning researchers. Almost all the formal logics applied in deductive planning are proposed for more general purpose than planning. Usually, the more general and the more expre...

The research on conditional planning rejects the assumptions that there is no uncertainty or incompleteness of knowledge with respect to the state and changes of the system the plans operate on. Without these assumptions the sequences of operations that achieve the goals depend on the initial state and the outcomes of nondeterministic changes in the system. This setting raises the questions of ...

Automation of planning techniques can potentially save a great deal of design and programming time, and can help robots design plans when human help is not available. Currently, the computational cost of machine planning algorithms prevents wide-spread use of these systems, and these costs are magni ed in multiagent systems. The most expensive and time-consuming aspect of multiagent systems, co...

The research on conditional planning rejects the assumptions that there is no uncertainty or incompleteness of knowledge with respect to the state and changes of the system the plans operate on. Without these assumptions the sequences of operations that achieve the goals depend on the initial state and the outcomes of nondeterministic changes in the system. This setting raises the questions of ...

In previous work (Bennett 1993 DeJong and Bennetl 1993) we proposed a machine learning approach called permissive planning to extend classical planning into the realm of real wor ld plan execution Our prior results have been favorable but empirical (Bennetl and DeJong 1991) Here we examine the analytic foundations of our empirical success We advance a formal account of realwor ld planning adequ...

Solving real planning problems requires to consider spatial and temporal information. Indeed, to be solved more efficiently many real world problems need to take the action duration, the instants of effects occurrences, the instants of requiring preconditions. . . and the space in which the mission is accomplished by defining the different actions zones and know the path between these zones int...

The influence of pre-retirement leisure activity patterns on retirement planning and attitudes toward retirement was investigated. Sixty male retirees answered a questionnaire designed to collect data regarding sociodemographic variables, the degree of preretirement planning, the type and extent of leisure participation before and after retirement, and attitudes about retirement. The results sh...

Bounded Intention Planning (BIP) [7] is a pruning approach for optimal planning with unary operators. BIP has the flavor of partial order reduction, which has recently found increasing interest for optimal planning [4, 6]. However, although BIP is claimed to be a variant of stubborn sets [3] in the original paper, no proof is given for this claim. In this paper, we shed light on the relationshi...