| | Scott Stern's School | Josh Tenenbaum's School | | :----------------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | | Focus | - Market: How environments shape choice/action set <br> - Strategy: How strategy guides entrepreneurs to make experimental choices among multiple paths under uncertainty and resource constraint | - Inference: How agents use hierarchical learning framework to form strong and flexible prior from limited data <br> - Action: How agents use beliefs and desire to make decisions under uncertainty and resource constraint | | Divergent Origins | Market Dynamics <br> - Incumbency and RछD Incentives (2000) <br> - When Does Start-Up Innovation Spur the Gale of Creative Destruction? (2002) <br> - Product Market and Market for Ideas (2003) <br> - Essays on Metrics in Innovation (2022) | Inference <br> - Bayesian Concept Learning (1999) <br> - Theory-Based Causal Induction (2007) <br> - Learning Grounded Causal Models (2007) <br> - Bayesian theory of mind: Modeling joint belief-desire attribution (2011) <br> - Towards More Human-Like Concept | | Convergent <br> Pathways | Entrepreneur's Strategic Choice <br> - Endogenous Appropriability (2018) <br> - Foundations of Entrepreneurial Strategy (2020) <br> - Choosing Technology: An En(2021) <br> - Commercializing Contrarian Ideas (2024) <br> - Bayesian Entrepreneurship (2024) <br> - Entrepreneurship: Choice and Strategy (2024) | Resource Rational Action <br> - One and Done? Optimal Decisions From Very Few Samples (2014) <br> - Computational Rationality: A Converging Paradigm (2015) <br> - The Naïve Utility Calculus (2016, 2020) <br> - Bayesian Models of Conceptual Development (2020) <br> - From World to Word Models (2023) <br> - Bayesian Models of Cognition (2024) | | Tools-Needs | - Need 1 Information-constrained opportunity valuation - A Bayesian model of how entrepreneurs allocate limited information-processing capacity when forming subjective beliefs about opportunities. (vs. behavioral bias) <br><br> - Need 2 Market-driven belief evolution - A resource-rational framework explaining how entrepreneurs update beliefs from limited market signals without full convergence to consensus (vs. shared prior assumed in gametheoretic models). | - Tool 1 Utility-based frameworks A language from control and decision theory (e.g. partially observable markov decision process) to rationalize agent's decision assuming infinite computational capacity. <br> - Tool 2 Resource-rational inference algorithms - Algorithms enabling optimal decisions under computational constraints using limited samples. <br> - Tool 3 Probabilistic programming platforms - Language, algorithm, community that integrates utility and resource-rational inference in unified computational architectures. |