AI agents maximize expected utility to achieve goals, a key concept in decision-making under uncertainty
Probabilistic reasoning is crucial for AI agents dealing with incomplete or uncertain information
6
21 reads
CURATED FROM
IDEAS CURATED BY
Giuseppe Biondi-Zoccai is a renowned expert in cardiology, medical research methodology and evidence synthesis
Stuart Russell and Peter Norvig's Artificial Intelligence: A Modern Approach (4th Edition) explores the development of AI systems, focusing on rational agents, machine learning, and decision-making under uncertainty. It emphasizes AI's shift from rule-based to learning systems, highlighting the ethical implications of AI control. The book is essential for understanding modern AI technologies and their societal impact.
“
Similar ideas to Utility Theory and Decision Making in AI
Decision making is a complex process, that engages both reasoning and emotions. Even the most emotional person uses rational thought when deciding, and even the most rational person is affected by emotions when making decisions.
Still, we often tend to highlight the negati...
Read & Learn
20x Faster
without
deepstash
with
deepstash
with
deepstash
Personalized microlearning
—
100+ Learning Journeys
—
Access to 200,000+ ideas
—
Access to the mobile app
—
Unlimited idea saving
—
—
Unlimited history
—
—
Unlimited listening to ideas
—
—
Downloading & offline access
—
—
Supercharge your mind with one idea per day
Enter your email and spend 1 minute every day to learn something new.
I agree to receive email updates