TH
T.R. Hinnerichs
Contributed
20 records found
Solving machine learning with machine learning
Exploiting Very Large-Scale Neighbourhood Search for synthesizing machine learning pipelines
This paper presents a comparative study of multiple algorithms that can be used to automatically search for high-performing pipelines on machine learning problems. These algorithms, namely Very Large-Scale Neighbourhood search (VLSN), Breadth-first search, Metropolis-Hastings, M
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Program Synthesis from Rewards with Probe
Adjusting Probe to Increase Exploration When Synthesising Programs from Rewards in Minecraft
Program synthesis is the task of generating a program that satisfies some specification. An important aspect of program synthesis is the method of specification. There are various ways in which a desired program can be specified, such as I/O examples, traces, and natural language
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Reward Based Program Synthesis for Minecraft
Adapting Program Synthesizers for Reward Evaluation and Leveraging Discovered Programs
Program synthesis is the task to construct a program that provably satisfies a given high-level specification. There are various ways in which a specification can be described. This research focuses on adapting the Probe synthesizer, traditionally reliant on input-output examples
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Reward Based Program Synthesis for Minecraft
Adapting Program Synthesizers for Reward Evaluation and Leveraging Discovered Programs
Program synthesis is the task to construct a program that provably satisfies a given high-level specification. There are various ways in which a specification can be described. This research focuses on adapting the Probe synthesizer, traditionally reliant on input-output examples
...
Reward Based Program Synthesis for Minecraft
Adapting Program Synthesizers for Reward Evaluation and Leveraging Discovered Programs
Program synthesis is the task to construct a program that provably satisfies a given high-level specification. There are various ways in which a specification can be described. This research focuses on adapting the Probe synthesizer, traditionally reliant on input-output examples
...
Reward Based Program Synthesis for Minecraft
Adapting Program Synthesizers for Reward Evaluation and Leveraging Discovered Programs
Program synthesis is the task to construct a program that provably satisfies a given high-level specification. There are various ways in which a specification can be described. This research focuses on adapting the Probe synthesizer, traditionally reliant on input-output examples
...
Program Synthesis from Rewards using Probe and FrAngel
Impact of Exploration-Exploitation Configurations on Probe and FrAngel in Minecraft
Program synthesis involves finding a program that meets the user intent, typically provided as input/output examples or formal mathematical specifications. This paper explores a novel specification in program synthesis - learning from rewards.
We explore existing synthesizers, P
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Program Synthesis from Rewards using Probe and FrAngel
Impact of Exploration-Exploitation Configurations on Probe and FrAngel in Minecraft
Program synthesis involves finding a program that meets the user intent, typically provided as input/output examples or formal mathematical specifications. This paper explores a novel specification in program synthesis - learning from rewards.
We explore existing synthesizers, P
...
Program Synthesis from Rewards using Probe and FrAngel
Impact of Exploration-Exploitation Configurations on Probe and FrAngel in Minecraft
Program synthesis involves finding a program that meets the user intent, typically provided as input/output examples or formal mathematical specifications. This paper explores a novel specification in program synthesis - learning from rewards.
We explore existing synthesizers, P
...
Program Synthesis from Rewards using Probe and FrAngel
Impact of Exploration-Exploitation Configurations on Probe and FrAngel in Minecraft
Program synthesis involves finding a program that meets the user intent, typically provided as input/output examples or formal mathematical specifications. This paper explores a novel specification in program synthesis - learning from rewards.
We explore existing synthesizers, P
...
Program Synthesis from Game Rewards Using FrAngel
Finding Complex Subprograms for Solving Minecraft
Program synthesis has been extensively used for automating code-related tasks, but it has yet to be applied in the realm of reward-based games. FrAngel is a component-based program synthesizer that addresses the aspects of exploration and exploitation, both important for the perf
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Program Synthesis from Game Rewards Using FrAngel
Finding Complex Subprograms for Solving Minecraft
Program synthesis has been extensively used for automating code-related tasks, but it has yet to be applied in the realm of reward-based games. FrAngel is a component-based program synthesizer that addresses the aspects of exploration and exploitation, both important for the perf
...
Program Synthesis from Game Rewards Using FrAngel
Finding Complex Subprograms for Solving Minecraft
Program synthesis has been extensively used for automating code-related tasks, but it has yet to be applied in the realm of reward-based games. FrAngel is a component-based program synthesizer that addresses the aspects of exploration and exploitation, both important for the perf
...
Program Synthesis from Game Rewards Using FrAngel
Finding Complex Subprograms for Solving Minecraft
Program synthesis has been extensively used for automating code-related tasks, but it has yet to be applied in the realm of reward-based games. FrAngel is a component-based program synthesizer that addresses the aspects of exploration and exploitation, both important for the perf
...
This paper investigates the performance of the A* algorithm in the field of automated machine learning using program synthesis. We designed a context-free grammar to create machine learning pipelines and came up with a cost function for A*. Two different experiments were done, th
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Machine learning pipelines encompass various sequential steps involved in tasks such as data extraction, preprocessing, model training, and deployment. Manual construction of these pipelines demands expert knowledge and can be time-consuming. To address this challenge, program sy
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Because of the growing presence of artificial intelligence, developers are looking for more efficient methods to construct machine learning algorithms. Program synthesizers allow us to produce algorithms consisting of scalers, feature selection and classifiers. Each of these pipe
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In AutoML, the search space of possible pipelines is often large and multidimensional. This makes it very important to use an efficient search algorithm. We measure the effectiveness of the Metropolis-Hastings algorithm (M-H) in a pipeline synthesis framework, when the search spa
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How convenient would it be to have an AI that relieves us programmers from the burden of coding? Program synthesis is a technique that achieves exactly that: it automatically generates simple programs that meet a given set of examples or adhere to a provided specification. This i
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Program synthesis remains largely unexplored in the context of playing games, where exploration and exploitation are crucial for solving tasks within complex environments. FrAngel is a program synthesis algorithm that addresses both of these aspects with its fragments used for th
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