Books like Bad choices by Ali Almossawi

Daniel Kahneman's "Thinking, Fast and Slow" explains how two distinct mental systems shape our judgments and decisions, offering insights into the biases that influence everyday choices.

Rolf Dobelli presents 99 concise chapters that explain everyday cognitive biases, showing how awareness can sharpen decision‑making at work and in life.

Explore how hidden psychological forces shape our economic decisions, from personal finance to the 2008 crisis, with Dan Ariely’s behavioral economics insights.

Barry Schwartz explains how an excess of choices can create anxiety, dissatisfaction, and paralysis, offering practical strategies to limit options and enhance satisfaction.

A deep dive into how behavioral economics reshaped our understanding of decision making through pioneering Israeli psychological research and its impact on evidence‑based policy.

A practical guide that compiles fifty decision‑making models from MBA curricula to help readers choose better answers, improve efficiency, and clarify personal goals.

Decision Theory = Probability + Utility Theory + + Universal Induction = Ockham + Bayes + Turing = = A Unified View of Artificial Intelligence This book presents sequential decision theory from a novel algorithmic information theory perspective. While the former is suited for active agents in known environments, the latter is suited for passive prediction in unknown environments. The book introduces these two well-known but very different ideas and removes the limitations by unifying them to one parameter-free theory of an optimal reinforcement learning agent embedded in an arbitrary unknown environment. Most if not all AI problems can easily be formulated within this theory, which reduces the conceptual problems to pure computational ones. Considered problem classes include sequence prediction, strategic games, function minimization, reinforcement and supervised learning. The discussion includes formal definitions of intelligence order relations, the horizon problem and relations to other approaches to AI. One intention of this book is to excite a broader AI audience about abstract algorithmic information theory concepts, and conversely to inform theorists about exciting applications to AI.