Goodwin, Richard
Monte Carlo Tree Search for Recipe Generation using GPT-2
Taneja, Karan, Segal, Richard, Goodwin, Richard
Automatic food recipe generation methods provide a creative tool for chefs to explore and to create new, and interesting culinary delights. Given the recent success of large language models (LLMs), they have the potential to create new recipes that can meet individual preferences, dietary constraints, and adapt to what is in your refrigerator. Existing research on using LLMs to generate recipes has shown that LLMs can be finetuned to generate realistic-sounding recipes. However, on close examination, these generated recipes often fail to meet basic requirements like including chicken as an ingredient in chicken dishes. In this paper, we propose RecipeMC, a text generation method using GPT-2 that relies on Monte Carlo Tree Search (MCTS). RecipeMC allows us to define reward functions to put soft constraints on text generation and thus improve the credibility of the generated recipes. Our results show that human evaluators prefer recipes generated with RecipeMC more often than recipes generated with other baseline methods when compared with real recipes.
Reports on the Twenty-First National Conference on Artificial Intelligence (AAAI-06) Workshop Program
Achtner, Wolfgang, Aimeur, Esma, Anand, Sarabjot Singh, Appelt, Doug, Ashish, Naveen, Barnes, Tiffany, Beck, Joseph E., Dias, M. Bernardine, Doshi, Prashant, Drummond, Chris, Elazmeh, William, Felner, Ariel, Freitag, Dayne, Geffner, Hector, Geib, Christopher W., Goodwin, Richard, Holte, Robert C., Hutter, Frank, Isaac, Fair, Japkowicz, Nathalie, Kaminka, Gal A., Koenig, Sven, Lagoudakis, Michail G., Leake, David B., Lewis, Lundy, Liu, Hugo, Metzler, Ted, Mihalcea, Rada, Mobasher, Bamshad, Poupart, Pascal, Pynadath, David V., Roth-Berghofer, Thomas, Ruml, Wheeler, Schulz, Stefan, Schwarz, Sven, Seneff, Stephanie, Sheth, Amit, Sun, Ron, Thielscher, Michael, Upal, Afzal, Williams, Jason, Young, Steve, Zelenko, Dmitry
The Workshop program of the Twenty-First Conference on Artificial Intelligence was held July 16-17, 2006 in Boston, Massachusetts. The program was chaired by Joyce Chai and Keith Decker. The titles of the 17 workshops were AIDriven Technologies for Service-Oriented Computing; Auction Mechanisms for Robot Coordination; Cognitive Modeling and Agent-Based Social Simulations, Cognitive Robotics; Computational Aesthetics: Artificial Intelligence Approaches to Beauty and Happiness; Educational Data Mining; Evaluation Methods for Machine Learning; Event Extraction and Synthesis; Heuristic Search, Memory- Based Heuristics, and Their Applications; Human Implications of Human-Robot Interaction; Intelligent Techniques in Web Personalization; Learning for Search; Modeling and Retrieval of Context; Modeling Others from Observations; and Statistical and Empirical Approaches for Spoken Dialogue Systems.
Reports on the Twenty-First National Conference on Artificial Intelligence (AAAI-06) Workshop Program
Achtner, Wolfgang, Aimeur, Esma, Anand, Sarabjot Singh, Appelt, Doug, Ashish, Naveen, Barnes, Tiffany, Beck, Joseph E., Dias, M. Bernardine, Doshi, Prashant, Drummond, Chris, Elazmeh, William, Felner, Ariel, Freitag, Dayne, Geffner, Hector, Geib, Christopher W., Goodwin, Richard, Holte, Robert C., Hutter, Frank, Isaac, Fair, Japkowicz, Nathalie, Kaminka, Gal A., Koenig, Sven, Lagoudakis, Michail G., Leake, David B., Lewis, Lundy, Liu, Hugo, Metzler, Ted, Mihalcea, Rada, Mobasher, Bamshad, Poupart, Pascal, Pynadath, David V., Roth-Berghofer, Thomas, Ruml, Wheeler, Schulz, Stefan, Schwarz, Sven, Seneff, Stephanie, Sheth, Amit, Sun, Ron, Thielscher, Michael, Upal, Afzal, Williams, Jason, Young, Steve, Zelenko, Dmitry
The Workshop program of the Twenty-First Conference on Artificial Intelligence was held July 16-17, 2006 in Boston, Massachusetts. The program was chaired by Joyce Chai and Keith Decker. The titles of the 17 workshops were AIDriven Technologies for Service-Oriented Computing; Auction Mechanisms for Robot Coordination; Cognitive Modeling and Agent-Based Social Simulations, Cognitive Robotics; Computational Aesthetics: Artificial Intelligence Approaches to Beauty and Happiness; Educational Data Mining; Evaluation Methods for Machine Learning; Event Extraction and Synthesis; Heuristic Search, Memory- Based Heuristics, and Their Applications; Human Implications of Human-Robot Interaction; Intelligent Techniques in Web Personalization; Learning for Search; Modeling and Retrieval of Context; Modeling Others from Observations; and Statistical and Empirical Approaches for Spoken Dialogue Systems.