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Questions and Answers
What does the transition function T in deterministic sequential planning represent?
In deterministic planning, the environment is dynamic and partially observable.
False
What is the goal of deterministic sequential planning?
To maximize cumulated rewards or minimize cumulated costs.
The cumulated reward is calculated using the formula ∑$!r!$ with a discount factor $𝛾$ such that ___ < $𝛾$ ≤ 1.
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Match the following components of deterministic planning with their descriptions:
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Why are very few deterministic games considered interesting?
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In deterministic sequential planning, rewards and costs are always treated equally.
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Study Notes
Deterministic Problems in Games
- Few deterministic games are interesting to play.
- Deterministic planning is used to solve subtasks for AI engines.
- Examples include finding building exits or routing to a target.
- Approximate and heuristic solutions for non-deterministic problems often rely on transforming the problem into a deterministic one.
- This involves assuming the opponent uses the same policy as the player, as in Go or chess.
Deterministic Sequential Planning
- Assumes static and fully observable environments.
- Includes a set of states S = {s1,..,sn}.
- Each state has a set of actions A(s).
- Has a reward function R: R(s) (if negative - considers a cost function).
- Includes a transition function T: S´A => S: t(s,a) = s’.
- The goal is to maximize cumulated rewards (minimize cumulated cost)
- The formula for cumulated reward/cost of the episode is: ∑$!"# 𝛾 !𝑟!with 0 < 𝛾 ≤ 1
- When 𝛾=1, all rewards count equally.
- When 𝛾 <1, rewards further in the future are valued less.
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Description
Explore the principles of deterministic games and planning methodologies used in AI. This quiz covers the characteristics of these games, the importance of planning in artificial intelligence, and techniques used to address non-deterministic problems. Test your knowledge on the theoretical frameworks that govern deterministic sequential planning.
