1. Making Simple Decisions
Chapter 16
Copyright, 1996 © Dale Carnegie & Associates, Inc.

2. Combining beliefs and desires
We can make decision based on probabilistic reasoning (Belief Networks), but it does not include what an gent wants.
An agent’s preferences between world states are captured by a utility function - it assigns a single number to express the desirability of a state.
Utilities are combined with the outcome probabilities for actions to give an expected utility for each action.
CS 471/598 by H. Liu

3. Simple decisions are one-shot decisions.
Expected utility
EU(A|E) =P(resulti(A)|E,Do(A))U (resulti(A))
Maximum expected utility - a rational agent should choose an action that maximizes the agent’s EU.
Simple decisions are one-shot decisions.
CS 471/598 by H. Liu

4. The basis of utility theory
Why should maximizing the average utility be so special?
Constraints on rational preferences are orderability, transitivity, continuity, substitutability, monotonicity, decomposability.
The six constraints form the axioms of utility theory.
The axioms of utility:
Utility principle
Maximum Expected Utility principle
CS 471/598 by H. Liu

5. Utility functions Utility functions map states to real numbers.
Utility theory has its roots in economics -> the utility of money
Risk averse
Risk seeking
Certainty equivalent
Risk neutral
Utility scales and utility assessment
Normalization
CS 471/598 by H. Liu

6. Decision networks Types of nodes Action-utility tables (Eq. 16.1)
Chance nodes
Decision nodes
Utility nodes
Action-utility tables (Eq. 16.1)
Evaluating decision networks
An algorithm (P 601)
CS 471/598 by H. Liu

7. The value of information
One of the most important parts of decision making is knowing what questions to ask.
To conduct expensive and critical tests or not depends on two factors:
Whether the different possible outcomes would make a significant difference to the optimal course of action
The likelihood of the various outcomes
Information value theory enables an agent to choose what information to acquire.
CS 471/598 by H. Liu

8. Decision-theoretic expert systems
The decision maker states preferences between outcomes.
The decision analyst enumerates the possible actions and outcomes and elicits preferences from the decision maker to determine the best course of action.
The addition of decision networks means that expert systems can be developed that recommend optimal decisions, reflecting the preferences of the user as well as the available evidence.
CS 471/598 by H. Liu

9. Summary
Probability theory describes what an agent should believe based on evidence
Utility theory describes what an agent wants
Decision theory puts the two together to describe what an agent should do
A rational agent should select actions that maximize its expected utility.
Decision networks provide a simple formalism for expressing and solving decision problems.
CS 471/598 by H. Liu