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T or F
1. An agent that uses minimax search, which assumes an enemy behaves optimally, may achieve
a better score when playing against a suboptimal enemy than the agent would against an optimal
enemy.
2. To guarantee the optimality of A* search, the heuristic function must never overestimate the
actual cost to reach the goal state.
3. Admissible heuristics are never derivable from the solution costs of subproblems.
4. The Turing test defines the conditions under which a machine can be said to be intelligent.
5. For a CSP, given a choice of variable, we want to consider the most constraint value first (the
one that rules out the most values in the remaining variables)

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  • 1. T or F 1. An agent that uses minimax search, which assumes an enemy behaves optimally, may achieve a better score when playing against a suboptimal enemy than the agent would against an optimal enemy. 2. To guarantee the optimality of A* search, the heuristic function must never overestimate the actual cost to reach the goal state. 3. Admissible heuristics are never derivable from the solution costs of subproblems. 4. The Turing test defines the conditions under which a machine can be said to be intelligent. 5. For a CSP, given a choice of variable, we want to consider the most constraint value first (the one that rules out the most values in the remaining variables)