By Narciso Martí-Oliet, José Meseguer (auth.), Remo Pareschi, Bertram Fronhöfer (eds.)

Reasoning is a vital part of clever platforms in fields like databases, good judgment programming, robotics, wisdom engineering, human/computer interfaces, programming environments, and so forth. actually the sort of approach has to deal with a altering global and its dynamics. for this reason it really is of significant value that reasoning needs to account for dealing with swap so as to be really invaluable in perform.

The publication includes numerous contributions to present methods of drawing close this challenge. at the one hand it surveys and synthesizes fresh study paintings, whereas nevertheless new examine effects are integrated. one of the themes handled are logics for reasoning approximately activities and making plans, trust revision and the reconciliation of logically conflicting inputs, resolving of conflicts via merging of data and matters within the evolution in object-oriented databases.

The e-book is geared toward the researcher and complicated pupil energetic during this field.

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**Additional resources for Dynamic Worlds: From the Frame Problem to Knowledge Management**

**Sample text**

Sn, a subset PM ~ M 8 , x ... x Msn, which can alternatively be viewed as a characteristic function PM : M 81 x ... x Msn --+ Bool to the two element Boolean algebra Bool. Satisfaction of a Horn clause in a model M can be expressed as the functional inequality (t) Ql(ul)M and ... and Qn(un)M ~ p(t)M between the corresponding interpretations in M as characteristic functions of the conjunction of the premises and of the conclusion. Horn logic is a particularly simple logic that does not use the full power of classical first order logic; it is therefore reasonable to allow interpretations of the predicate symbols p as "characteristic functions" into a partially ordered set M Prop of "propositions" which can vary from model to model.

Ops g y : -> Gene op p : Gene Gene -> Pea [comm] ops yellow green : -> Pea . var G : Gene . eq p(y,y) yellow eq p(g,G) = green . endfm Now we define the effect of crossing two peas. The genes determining the color are split and combined with the genes from the other pea. mod GENETICS is extending PEAS sort State . subsort Pea < State op 0 : -> State . op -#- : State State -> State [assoc comm id: 0] . op c : Pea Pea -> Pea . vars W X Y Z : Gene rl c(p(W ,X) ,p(Y ,Z)) => p(W, Y) # p(W ,Z) # p(X, Y) # p(X,Z).

In the order-sorted case such symbols have ranks f : s 1 ... Sn -+ s, and p : s1 ... sn, specified by strings of sorts in the poset of sorts S. Models are F-algebras M together with, for each predicate symbol p: s1 ... Sn, a subset PM ~ M 8 , x ... x Msn, which can alternatively be viewed as a characteristic function PM : M 81 x ... x Msn --+ Bool to the two element Boolean algebra Bool. Satisfaction of a Horn clause in a model M can be expressed as the functional inequality (t) Ql(ul)M and ...