Search Results

Symbolic Regression via Deep Reinforcement Learning Enhanced Genetic Programming Seeding

1 code implementation NeurIPS 2021

Symbolic regression is the process of identifying mathematical expressions that fit observed output from a black-box process.

Combinatorial Optimization regression +3

Combining Reinforcement Learning and Constraint Programming for Combinatorial Optimization

1 code implementation2 Jun 2020

In this work, we propose a general and hybrid approach, based on DRL and CP, for solving combinatorial optimization problems.

Combinatorial Optimization Portfolio Optimization +3

From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihood

3 code implementations ACL 2017

Our goal is to learn a semantic parser that maps natural language utterances into executable programs when only indirect supervision is available: examples are labeled with the correct execution result, but not the program itself.

reinforcement-learning Reinforcement Learning (RL) +1

SeaPearl: A Constraint Programming Solver guided by Reinforcement Learning

1 code implementation18 Feb 2021

This paper presents the proof of concept for SeaPearl, a new CP solver implemented in Julia, that supports machine learning routines in order to learn branching decisions using reinforcement learning.

BIG-bench Machine Learning Combinatorial Optimization +2

Automated quantum programming via reinforcement learning for combinatorial optimization

1 code implementation21 Aug 2019

Relative to a set of randomly generated problem instances, agents trained through reinforcement learning techniques are capable of producing short quantum programs which generate high quality solutions on both types of quantum resources.

Combinatorial Optimization reinforcement-learning +1

Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision

2 code implementations ACL 2017

Harnessing the statistical power of neural networks to perform language understanding and symbolic reasoning is difficult, when it requires executing efficient discrete operations against a large knowledge-base.

Feature Engineering Structured Prediction

IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures

21 code implementations ICML 2018

In this work we aim to solve a large collection of tasks using a single reinforcement learning agent with a single set of parameters.

Ranked #3 on Atari Games on Atari 2600 Skiing (using extra training data)

Atari Games reinforcement-learning +1

Memory Augmented Policy Optimization for Program Synthesis and Semantic Parsing

4 code implementations NeurIPS 2018

We present Memory Augmented Policy Optimization (MAPO), a simple and novel way to leverage a memory buffer of promising trajectories to reduce the variance of policy gradient estimate.

Combinatorial Optimization Program Synthesis +2

NICE: Robust Scheduling through Reinforcement Learning-Guided Integer Programming

1 code implementation24 Sep 2021

We compare NICE with (1) a baseline integer programming formulation that produces a feasible crew schedule, and (2) a robust integer programming formulation that explicitly tries to minimize the impact of disruptions.

reinforcement-learning Reinforcement Learning (RL) +1

A Reinforcement Learning Environment for Mathematical Reasoning via Program Synthesis

1 code implementation15 Jul 2021

We convert the DeepMind Mathematics Dataset into a reinforcement learning environment by interpreting it as a program synthesis problem.

Mathematical Reasoning Program Synthesis +2