AI News, Lecture 1 CS6800 Artificial Intelligence: artificial intelligence

Computer Science, PhD

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Introduction to Artificial Intelligence Evolutionary Computing Henry Kautz.

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Myopic Local Search The local search methods we have discussed so far are myopic – they only look at the immediate neighborhood of a single state at any one time Simple Parallelism: run many searches in parallel with different random seeds –Prob(Success) = 1 – Prob(Run Fails) k –E.g.: Prob(Run Fails) = 90%, k = 10  Prob(Success) = 65% {

'name': 'Myopic Local Search The local search methods we have discussed so far are myopic – they only look at the immediate neighborhood of a single state at any one time Simple Parallelism: run many searches in parallel with different random seeds –Prob(Success) = 1 – Prob(Run Fails) k –E.g.: Prob(Run Fails) = 90%, k = 10  Prob(Success) = 65%',

'description': 'Myopic Local Search The local search methods we have discussed so far are myopic – they only look at the immediate neighborhood of a single state at any one time Simple Parallelism: run many searches in parallel with different random seeds –Prob(Success) = 1 – Prob(Run Fails) k –E.g.: Prob(Run Fails) = 90%, k = 10  Prob(Success) = 65%',

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'name': 'Genetic algorithms A successor state is generated by combining two parent states Start with k randomly generated states (population) A state is represented as a string over a finite alphabet (often a string of 0s and 1s) Evaluation function (fitness function).',

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'name': 'Example: 8-Queens Fitness function: number of non-attacking pairs of queens (min = 0, max = 8 × 7/2 = 28) 24/( ) = 31% 23/( ) = 29% etc Normalized Fitness',

'description': 'Example: 8-Queens Fitness function: number of non-attacking pairs of queens (min = 0, max = 8 × 7/2 = 28) 24/( ) = 31% 23/( ) = 29% etc Normalized Fitness',

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“ Normal” crossover operators will often lead to inadmissible solutions Many specialised operators have been devised which focus on combining order or adjacency information from the two parents Crossover operators for permutations 1 2 3 4 5 5 4 3 2 1 1 2 3 2 1 5 4 3 4 5 {

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Computational Bottleneck Consider networks for sorting 16 numbers: every child must be tested on 2 16 inputs Cost of doing all these tests comprises nearly all of the computation time Strategies: –Parallelize evaluation of children [1,000 node cluster] –Use special hardware (FPGA) to evaluate [Koza et al 1997] {

'name': 'Computational Bottleneck Consider networks for sorting 16 numbers: every child must be tested on 2 16 inputs Cost of doing all these tests comprises nearly all of the computation time Strategies: –Parallelize evaluation of children [1,000 node cluster] –Use special hardware (FPGA) to evaluate [Koza et al 1997]',

'description': 'Computational Bottleneck Consider networks for sorting 16 numbers: every child must be tested on 2 16 inputs Cost of doing all these tests comprises nearly all of the computation time Strategies: –Parallelize evaluation of children [1,000 node cluster] –Use special hardware (FPGA) to evaluate [Koza et al 1997]',

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Swarm Algorithms, Briefly Idea: –Each insect in a swarm is local search process –At each step, each insect: Looks around its neighborhood Decides which direction looks best Communicates what it found out to (some of) the other insects According to a random coin flip, –Moves in the direction that looks best locally –Moves in the best direction it hears about –Moves in some weighted combination of the above {

'name': 'Swarm Algorithms, Briefly Idea: –Each insect in a swarm is local search process –At each step, each insect: Looks around its neighborhood Decides which direction looks best Communicates what it found out to (some of) the other insects According to a random coin flip, –Moves in the direction that looks best locally –Moves in the best direction it hears about –Moves in some weighted combination of the above',

'description': 'Swarm Algorithms, Briefly Idea: –Each insect in a swarm is local search process –At each step, each insect: Looks around its neighborhood Decides which direction looks best Communicates what it found out to (some of) the other insects According to a random coin flip, –Moves in the direction that looks best locally –Moves in the best direction it hears about –Moves in some weighted combination of the above',

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