Insights topic
14 articles on this topic.
How economics, psychology, neuroscience, computer science, engineering, mathematics and operations research each contributed to the methods machines use to make decisions.
10 min read
Many decisions must be made without knowing the true situation. How beliefs, Bayesian filters, Kalman and particle filters and belief-state planning handle partial observability.
10 min read
Bayesian networks represent uncertain relationships as a map of influences. How they work, how they support diagnosis and prediction, and what they can and cannot tell you about cause and effect.
10 min read
Automated systems and people both optimise what they are measured on. How objectives go wrong, how to balance multiple goals with trade-off analysis, and how to design rewards and KPIs that work.
10 min read
When team members share a goal but each sees only part of the picture, coordination is surprisingly hard. Lessons from collaborative agents research for designing teams, roles and communication.
10 min read
A plain-English introduction to how people and machines make decisions when outcomes, models, situations and other actors are uncertain, and the main ways to design decision systems.
12 min read
Your best choice often depends on what others do. A plain-English guide to dominant strategies, Nash equilibrium, the prisoner's dilemma and how people really reason about each other.
10 min read
Systems can learn by copying expert demonstrations. How behavioural cloning, cascading errors, expert correction and inverse reinforcement learning work, and what they teach about know-how.
10 min read
When problems are too large to solve completely, decision makers plan from the current situation by looking a few steps ahead. How lookahead, rollouts, Monte Carlo tree search and re-planning work.
10 min read
Reinforcement learning lets systems learn decision strategies by trial and error, guided by rewards. A plain-English guide to how it works, its main methods, its risks and where it fits in business.
10 min read
Many decisions are steps in a sequence. A plain-English guide to Markov decision processes, policies, value functions, discounting and dynamic programming, with business examples.
10 min read
How to validate automated decision systems: performance metrics, rare-event simulation, robustness to model errors, trade-off analysis, adversarial testing and responsible deployment.
10 min read
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