@InProceedings{spark16-08,
  author =   {Rami Matloob and Mikhail Soutchanski},
  title =    {Exploring Organic Synthesis with State-of-the-Art Planning Techniques},
  abstract = {We explore different techniques to solve the computationally challenging, but practically important organic synthesis problem. This problem requires finding a sequence of reactions producing the target molecule from a set of given initial molecules. This problem is often used on exams to test the problem solving skills of students who study generic reactions in organic chemistry courses. This problem is also relevant in industry. In a quest to find a more efficient way to solve a set of benchmark problems, we start by explaining how an organic synthesis problem can be formulated as a planning problem in PDDL. We then demonstrate how state-of-the-art planners such as SASE, Madagascar and SatPlan -- that reduce a bounded planning problem to SAT -- can only encode a fraction of the benchmark problems, due to their complexity. We also explore the recently developed action schema splitting approach that splits action schemas into several sub-actions with a shorter interface thereby alleviating somewhat the grounding problem. We assess experimentally performance of the Fast Downward planning system for different splitting values and compare the results with our original non split domain. For the finest split domain, where the modified action schemas have the smallest number of arguments, we investigate performance of Fast Downward depending on different heuristics. Our research continues the work initiated in the paper "Modeling Organic Chemistry and Planning Organic Synthesis" that has been recently published by Arman Masoumi, Megan Antoniazzi and Mikhail Soutchanski (GCAI-2015). In comparison to this previous work, where only the simplest instances could be solved due to the grounding problem from instantiation of actions with atoms, we explore several promising techniques and obtain interesting experimental results for the benchmark problems derived from the real MIT organic chemistry exams of varying complexity. No previous background in chemistry is required to understand our paper since we explain all the basics},
  keywords = {Novel domain and challenge problems, Experimental assessment of existing technologies, Modeling and domain model acquisition, Reduction of planning to SAT Action schema, splitting Fast Downward}
}

{"_id":"TYLrcmwz5CAYpa3E4","bibbaseid":"matloob-soutchanski-exploringorganicsynthesiswithstateoftheartplanningtechniques","downloads":0,"creationDate":"2016-04-07T22:01:23.439Z","title":"Exploring Organic Synthesis with State-of-the-Art Planning Techniques","author_short":["Matloob, R.","Soutchanski, M."],"year":null,"bibtype":"inproceedings","biburl":"icaps16.icaps-conference.org/spark16.bib","bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"firstnames":["Rami"],"propositions":[],"lastnames":["Matloob"],"suffixes":[]},{"firstnames":["Mikhail"],"propositions":[],"lastnames":["Soutchanski"],"suffixes":[]}],"title":"Exploring Organic Synthesis with State-of-the-Art Planning Techniques","abstract":"We explore different techniques to solve the computationally challenging, but practically important organic synthesis problem. This problem requires finding a sequence of reactions producing the target molecule from a set of given initial molecules. This problem is often used on exams to test the problem solving skills of students who study generic reactions in organic chemistry courses. This problem is also relevant in industry. In a quest to find a more efficient way to solve a set of benchmark problems, we start by explaining how an organic synthesis problem can be formulated as a planning problem in PDDL. We then demonstrate how state-of-the-art planners such as SASE, Madagascar and SatPlan – that reduce a bounded planning problem to SAT – can only encode a fraction of the benchmark problems, due to their complexity. We also explore the recently developed action schema splitting approach that splits action schemas into several sub-actions with a shorter interface thereby alleviating somewhat the grounding problem. We assess experimentally performance of the Fast Downward planning system for different splitting values and compare the results with our original non split domain. For the finest split domain, where the modified action schemas have the smallest number of arguments, we investigate performance of Fast Downward depending on different heuristics. Our research continues the work initiated in the paper \"Modeling Organic Chemistry and Planning Organic Synthesis\" that has been recently published by Arman Masoumi, Megan Antoniazzi and Mikhail Soutchanski (GCAI-2015). In comparison to this previous work, where only the simplest instances could be solved due to the grounding problem from instantiation of actions with atoms, we explore several promising techniques and obtain interesting experimental results for the benchmark problems derived from the real MIT organic chemistry exams of varying complexity. No previous background in chemistry is required to understand our paper since we explain all the basics","keywords":"Novel domain and challenge problems, Experimental assessment of existing technologies, Modeling and domain model acquisition, Reduction of planning to SAT Action schema, splitting Fast Downward","bibtex":"@InProceedings{spark16-08,\r\n author = {Rami Matloob and Mikhail Soutchanski},\r\n title = {Exploring Organic Synthesis with State-of-the-Art Planning Techniques},\r\n abstract = {We explore different techniques to solve the computationally challenging, but practically important organic synthesis problem. This problem requires finding a sequence of reactions producing the target molecule from a set of given initial molecules. This problem is often used on exams to test the problem solving skills of students who study generic reactions in organic chemistry courses. This problem is also relevant in industry. In a quest to find a more efficient way to solve a set of benchmark problems, we start by explaining how an organic synthesis problem can be formulated as a planning problem in PDDL. We then demonstrate how state-of-the-art planners such as SASE, Madagascar and SatPlan -- that reduce a bounded planning problem to SAT -- can only encode a fraction of the benchmark problems, due to their complexity. We also explore the recently developed action schema splitting approach that splits action schemas into several sub-actions with a shorter interface thereby alleviating somewhat the grounding problem. We assess experimentally performance of the Fast Downward planning system for different splitting values and compare the results with our original non split domain. For the finest split domain, where the modified action schemas have the smallest number of arguments, we investigate performance of Fast Downward depending on different heuristics. Our research continues the work initiated in the paper \"Modeling Organic Chemistry and Planning Organic Synthesis\" that has been recently published by Arman Masoumi, Megan Antoniazzi and Mikhail Soutchanski (GCAI-2015). In comparison to this previous work, where only the simplest instances could be solved due to the grounding problem from instantiation of actions with atoms, we explore several promising techniques and obtain interesting experimental results for the benchmark problems derived from the real MIT organic chemistry exams of varying complexity. No previous background in chemistry is required to understand our paper since we explain all the basics},\r\n keywords = {Novel domain and challenge problems, Experimental assessment of existing technologies, Modeling and domain model acquisition, Reduction of planning to SAT Action schema, splitting Fast Downward}\r\n}\r\n\r\n","author_short":["Matloob, R.","Soutchanski, M."],"key":"spark16-08","id":"spark16-08","bibbaseid":"matloob-soutchanski-exploringorganicsynthesiswithstateoftheartplanningtechniques","role":"author","urls":{},"keyword":["Novel domain and challenge problems","Experimental assessment of existing technologies","Modeling and domain model acquisition","Reduction of planning to SAT Action schema","splitting Fast Downward"],"metadata":{"authorlinks":{}}},"search_terms":["exploring","organic","synthesis","state","art","planning","techniques","matloob","soutchanski"],"keywords":["novel domain and challenge problems","experimental assessment of existing technologies","modeling and domain model acquisition","reduction of planning to sat action schema","splitting fast downward"],"authorIDs":[],"dataSources":["jaTZy22GuvTvLRhXH","jQBA6tLb2aZ6MhQEz"]}