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alpha-beta pruningthus we can prune via the alpha-beta method it makes means to perform a depth-first search requiring the minimax principle just
general principles of pruningthe general principles are such that1 given a node n that can be chosen by player one thus if there is another node x
pruning - artificial intelligencerecall which pruning a search space means deciding that there certain branches to should not be explored moreover if
example of the horizon problemit is also worth bearing in mind the horizon problem however a game-playing agent cannot see much far satisfactory into
main problems with evaluation functionssuperlatively evaluation functions should be quick calculates wherever is chance they take a long time to
evaluation functionsevaluation functions calculate approximately the score which can be prove of guaranteed if a particular world state is reached
depth in cutoff searchthe depth is chosen in advance to certify in which the agent does not capture much more long to choose a move however if it has
cutoff search to require a mini and max search in a game on stage situation is in which all we have is just do that programme our agent to look at
minimax searchalways notice there that the process above was in order for player one to choose his and her first move for that the whole entire
game playingwe have now dispensed with the necessary background material for ai problem solving techniques and we just considered to looking at
representation scheme in aibullits fairly trouble-free to represent knowledge in this way it allows us to be expressive enough to represent largely
multiple valued logicsmultiple valued logics where altered types of truth value such as unknown are may be allowed these have some of the particular
fuzzy logicin the logics we are here described above what we have been concerned with truth whether propositions and sentences are true moreover with
higher order predicate logic in the very first order predicate logic we are only allowed to quantify over objects if we are considered to allow
first order predicate logic this is a more expressive logic because it is mostly builds on propositional logic by allowing us to needs as constants
propositional logicthis is a fairly restrictive logic that allows us to be write sentences about notpropositions - statements about the world -
logical representationsif all human beings spoke the same language there would be a much more less misunderstanding in the world the problem
knowledge representationto recap we now have some characterizations of ai that when an ai problem arises you will be able to put all into context
assessing heuristic searchesgiven a particular problem you want to build an agent to solve so there may be more than one way of justifying it as a
common problem with hill climbingan alternative way of justifying the problem is that the states are boards with 8 queens already on them so an
hill climbing - artificial intelligenceas weve seen in some problems finding the search path from primary to goal state is the point of the exercise
random search - artificial intelligencesome problems to be solved by a search agent are more creative in nature for example like in writing poetry in
simulated annealingone way to get around the problem of local maxima and related problems like ridges and plateaux in hill climbing is to allow the
ida search - artificial intelligencea search is a sophisticated and successful search strategy in fact a problem with a search is that it must keep
a search - artificial intelligencea search in the combines is the best parts of uniform cost search namely the fact that its optimal and complete and