Algorithmic Decision Processes

no code implementations • 5 May 2023 • Carlo Baldassi, Fabio Maccheroni, Massimo Marinacci, Marco Pirazzini

We develop a full-fledged analysis of an algorithmic decision process that, in a multialternative choice problem, produces computable choice probabilities and expected decision times.

Ergodic Annealing

no code implementations • 1 Aug 2020 • Carlo Baldassi, Fabio Maccheroni, Massimo Marinacci, Marco Pirazzini

Simulated Annealing is the crowning glory of Markov Chain Monte Carlo Methods for the solution of NP-hard optimization problems in which the cost function is known.

reinforcement-learning Reinforcement Learning (RL)

Multialternative Neural Decision Processes

no code implementations • 3 May 2020 • Carlo Baldassi, Simone Cerreia-Vioglio, Fabio Maccheroni, Massimo Marinacci, Marco Pirazzini

We introduce an algorithmic decision process for multialternative choice that combines binary comparisons and Markovian exploration.