Agent Theories, Architectures, and Languages: A Survey <s> Moore -knowledge and action <s> Abstract : Most work on planning and problem solving within the field of artificial intelligence assumes that the agent has complete knowledge of all relevant aspects of the problem domain and problem situation In the real world, however, planning and acting must frequently be performed without complete knowledge. This imposes two additional burdens on an intelligent agent trying to act effectively. First, when the agent entertains a plan for achieving some goal, he must consider not only whether the physical prerequisites of the plan have been satisfied, but also whether he has all the information necessary to carry out the plan. Second, he must be able to reason about what be can do to obtain necessary information that he lacks. In this paper, we present a theory of action in which these problems are taken into account, showing how to formalize both the knowledge prerequisites of action and the effects of action on knowledge. <s> BIB001 </s> Agent Theories, Architectures, and Languages: A Survey <s> Moore -knowledge and action <s> Abstract Agents who operate in complex environments must often construct plans on the basis of incomplete knowledge. In such situations, the successful agent must incorporate into his plans actions which obtain information. These plans are intrinsically sketchy to begin with and become more specified as the agent proceeds through his plan. A theory which allows for such flexible planning will have to provide solutions to two problems: (1) how can an agent reason that he knows how to perform an action? (Knowledge Preconditions Problem for Actions) and (2) if an agent must construct an underspecified plan due to incomplete knowledge, when can we say that he can successfully execute his plan? (Knowledge Preconditions Problem for Plans) This paper provides solutions to both these problems. We develop a robust and highly expressive theory of action and planning which allows for actions of varying granularity, primitive as well as complex acts, multi-agent plans, and partially specified plans. We demonstrate that this theory lends itself in a natural manner to solutions to the Knowledge Preconditions Problems. <s> BIB002 </s> Agent Theories, Architectures, and Languages: A Survey <s> Moore -knowledge and action <s> For reversal development of an electrical potential pattern formed by imagewise exposure of a uniformly charged photoconductive layer, the charging of the layer is restricted to such a level below its breakdown voltage that the contact between the photoconductive layer and the toner powder used in the development step is insulating, and a magnetisable and inductively attractable toner powder is applied for the development. The toner powder is applied by means of a magnetic brush device comprising a conductive development roller which is provided with an electrical potential suited for reversal development. Preferably the photoconductive layer is charged to a level of at most 35-75% of its breakdown voltage, and a scorotron preferably is used for the charging. The photoconductive layer may comprise a photoconductive polymer and/or a bisazo pigment as photosensitive compound, or may be a layer of "pink" zinc oxide dispersed in a binder. <s> BIB003
Moore was in many ways a pioneer of the use of logics for capturing aspects of agency BIB001 . His main concern was the study of knowledge pre-conditions for actions -the question of what an agent needs to  ). This formalism allowed for the possibility of an agent having incomplete information about how to achieve some goal, and performing actions in order to find out how to achieve it. Critiques of the formalism (and attempts to improve on it) may be found in BIB002 BIB003 .