Simulation-Based Optimization for Material Dispatching in a Retailer Network. - Ganesh Subramaniam; Abhijit Gosavi (WSC, 2004)

Reinforcement learning for long-run average cost. - Abhijit Gosavi (Eur. J. Oper. Res., 2004)

A Reinforcement Learning Algorithm Based on Policy Iteration for Average Reward: Empirical Results with Yield Management and Convergence Analysis. - Abhijit Gosavi (Mach. Learn., 2004)

A risk-sensitive approach to total productive maintenance. - Abhijit Gosavi (Autom., 2006)

Boundedness of iterates in Q-Learning. - Abhijit Gosavi (Syst. Control. Lett., 2006)

Simulation-based optimisation for material dispatching in Vendor-Managed Inventory systems. - Ganesh Subramaniam; Abhijit Gosavi (Int. J. Simul. Process. Model., 2007)

Simulation optimization for revenue management of airlines with cancellations and overbooking. - Abhijit Gosavi; Emrah Ozkaya; Aykut F. Kahraman (OR Spectr., 2007)

On step sizes, stochastic shortest paths, and survival probabilities in Reinforcement Learning. - Abhijit Gosavi (WSC, 2008)

Stochastic Modeling of an Automated Guided Vehicle System With One Vehicle and a Closed-Loop Path. - Aykut F. Kahraman; Abhijit Gosavi; Karla J. Oty (IEEE Trans Autom. Sci. Eng., 2008)

Reinforcement Learning for Model Building and Variance-penalized Control. - Abhijit Gosavi (WSC, 2009)

Reinforcement Learning: A Tutorial Survey and Recent Advances. - Abhijit Gosavi (INFORMS J. Comput., 2009)

Finite horizon Markov control with one-step variance penalties. - Abhijit Gosavi (Allerton, 2010)

Model-building semi-Markov adaptive critics. - Abhijit Gosavi; Susan L. Murray; Jiaqiao Hu (ADPRL, 2011)

Stochastic policy search for variance-penalized semi-Markov control. - Abhijit Gosavi; Mandar Purohit (WSC, 2011)

On the distribution of the number stranded in bulk-arrival, bulk-service queues of the M/G/1 form. - Aykut F. Kahraman; Abhijit Gosavi (Eur. J. Oper. Res., 2011)

Approximate Policy Iteration for Semi-Markov Control Revisited. - Abhijit Gosavi (Complex Adaptive Systems, 2011)

Approximate Policy Iteration for Markov Control Revisited. - Abhijit Gosavi (Complex Adaptive Systems, 2012)

Relative value iteration for average reward semi-Markov control via simulation. - Abhijit Gosavi (WSC, 2013)

Beyond exponential utility functions: A variance-adjusted approach for risk-averse reinforcement learning. - Abhijit Gosavi; Sajal K. Das 001; Susan L. Murray (ADPRL, 2014)

How to Rein in the Volatile Actor: A New Bounded Perspective. - Abhijit Gosavi (Complex Adaptive Systems, 2014)

Variance-penalized Markov decision processes: dynamic programming and reinforcement learning techniques. - Abhijit Gosavi (Int. J. Gen. Syst., 2014)

Analyzing Responses from Likert Surveys and Risk-adjusted Ranking: A Data Analytics Perspective. - Abhijit Gosavi (Complex Adaptive Systems, 2015)

Solving Markov decision processes with downside risk adjustment. - Abhijit Gosavi; Anish Parulekar (Int. J. Autom. Comput., 2016)

Predicting Response of Risk-Seeking Systems During Project Negotiations in a System of Systems. - Abhijit Gosavi; Siddhartha Agarwal; Cihan H. Dagli (IEEE Syst. J., 2017)

A bounded actor-critic reinforcement learning algorithm applied to airline revenue management. - Ryan J. Lawhead; Abhijit Gosavi (Eng. Appl. Artif. Intell., 2019)

The Actor-Critic Algorithm for Infinite Horizon Discounted Cost Revisited. - Abhijit Gosavi (WSC, 2020)

Discrete-Event-Based Simulation Model for Performance Evaluation of Post-Earthquake Restoration in a Smart City. - Abhijit Gosavi; Giacomo Fraioli; Lesley H. Sneed; Nathaniel Tasker (IEEE Trans. Engineering Management, 2020)

On general multi-server queues with non-poisson arrivals and medium traffic: a new approximation and a COVID-19 ventilator case study. - Carlos Chaves; Abhijit Gosavi (Oper. Res., 2022)

Maintenance optimization in a digital twin for Industry 4.0. - Abhijit Gosavi; Vy K. Le (Ann. Oper. Res., 2024)

Deep reinforcement learning for approximate policy iteration: convergence analysis and a post-earthquake disaster response case study. - Abhijit Gosavi; Lesley H. Sneed; L. A. Spearing (Optim. Lett., 2024)