Lecture � CS182 Intelligent machines

Greg Detre

@14:30 on Wednesday, October 02, 2002

 

Review of CSP

prune search space

forward searching � trying to realise that you have a conflict higher up the tree rather than waiting till you get the bottom

arc consistency � assign values to a subset of variables, already doing some forward checking (1-consistency), also check constraints in the unassigned subset, all the way up to k-consistency (where you�re checking everything)

 

heuristics

find the one with the largest domain size

find which one is most constrained

use databases � there must be some trade-off between space and time that has been studied

least constraining value

 

heavy tails

use randomisation

 

Local search

complete state formulation � specifies a valuable for every variable while you�re searching

random walk is complete � if all of space is reachable � so it dpeends on your local state operator

ridge � although the points are close in state space, they�re unreachable as neighbours because of your local operator operator representation

the heuristic repair search solves the million queens in c. 50 steps � astonishing � that�s 106x106

provably you will find the global optimum (with high probability???) with simulated annealing if you move the temperature down slowly enough

it�s called �annealing� because it looks like an energy term

you can say these are complete + optimal, but they don�t know when they�ve found the global optimum � unlike systematic searches, because they maintain bounds

Tabu search

�???

Mitzenmacher � used it to find a new sequencing for an amino acid chain

helps to avoid cycles

Cooperative search (Clearwater et al.)

originated from imagining multi-agent environment

exchange hints with each other to help solve the problem, and decide when to use these hints

�???

 

GAs

think of crossovers as an exchange of hints

for crossover to work well, there has to be some modularity to your representation so that breaking it up into chunks helps

GAs don�t usually do as well as other equivalent algorithms

 

key local search ideas

communication (reachability)

diversification

intensification

 

 

 

 

Questions

largest domain size vs most constrained???

is stochastic beam search different from GAs at all???

y, it doesn�t derive from two parents

how many 8-queens solutions???

complete (vs optimal)???

in cooperative search, what�s a hint??? related to GA crossover