Sequential Decision Making

Benchmarks archive 2025-07-28

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Libraries

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Datasets archive 2025-07-28

1 dataset whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

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Most implemented papers archive 2025-07-28

30 shown of 351 papers with code (1,210 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Deep Reinforcement Learning for Unsupervised Video Summarization with Diversity-Representativeness Reward
  29 Dec 2017 6 repositories listed Syntology ran 1 of 1 samples · 0 unverified
  Video summarization aims to facilitate large-scale video browsing by producing short, concise summaries that are diverse and representative of original videos.
• Reflexion: Language Agents with Verbal Reinforcement Learning
  20 Mar 2023 5 repositories listed Syntology ran 2 of 9 samples · 7 unverified
  Large language models (LLMs) have been increasingly used to interact with external environments (e.
• IQ-Learn: Inverse soft-Q Learning for Imitation
  23 Jun 2021 5 repositories listed Syntology ran 2 of 3 samples · 1 unverified · 3 pointer-only (licence)
  In many sequential decision-making problems (e.
• Deep Reinforcement Learning based Recommendation with Explicit User-Item Interactions Modeling
  29 Oct 2018 5 repositories listed
  The DRR framework treats recommendation as a sequential decision making procedure and adopts an "Actor-Critic" reinforcement learning scheme to model the interactions between the users and recommender systems, which can…
• Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling
  26 Feb 2018 4 repositories listed
  At the same time, advances in approximate Bayesian methods have made posterior approximation for flexible neural network models practical.
• Learning Multi-Level Hierarchies with Hindsight
  4 Dec 2017 4 repositories listed
  Hierarchical agents have the potential to solve sequential decision making tasks with greater sample efficiency than their non-hierarchical counterparts because hierarchical agents can break down tasks into sets of…
• Thinking Fast and Slow with Deep Learning and Tree Search
  23 May 2017 4 repositories listed
  Sequential decision making problems, such as structured prediction, robotic control, and game playing, require a combination of planning policies and generalisation of those plans.
• Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization
  3 Oct 2022 3 repositories listed
  To help answer this, we first introduce an open-source modular library, RL4LMs (Reinforcement Learning for Language Models), for optimizing language generators with RL.
• Deep Reinforcement Learning for Imbalanced Classification
  5 Jan 2019 3 repositories listed Syntology ran 0 of 6 samples · 6 unverified
  The agent finally finds an optimal classification policy in imbalanced data under the guidance of specific reward function and beneficial learning environment.
• A2-RL: Aesthetics Aware Reinforcement Learning for Image Cropping
  14 Sep 2017 3 repositories listed
  Image cropping aims at improving the aesthetic quality of images by adjusting their composition.
• An Alternative Softmax Operator for Reinforcement Learning
  16 Dec 2016 3 repositories listed
  A softmax operator applied to a set of values acts somewhat like the maximization function and somewhat like an average.
• Model-Free Episodic Control
  14 Jun 2016 3 repositories listed Syntology ran 0 of 1 samples · 1 unverified
  State of the art deep reinforcement learning algorithms take many millions of interactions to attain human-level performance.
• Multi-Agent Reinforcement Learning for Autonomous Driving: A Survey
  19 Aug 2024 2 repositories listed
  Reinforcement Learning (RL) is a potent tool for sequential decision-making and has achieved performance surpassing human capabilities across many challenging real-world tasks.
• Scalable Exploration via Ensemble++
  18 Jul 2024 2 repositories listed Syntology ran 5 of 8 samples · 3 unverified · 8 pointer-only (licence)
  Thompson Sampling is a principled method for balancing exploration and exploitation, but its real-world adoption faces computational challenges in large-scale or non-conjugate settings.
• Sym-Q: Adaptive Symbolic Regression via Sequential Decision-Making
  7 Feb 2024 2 repositories listed
  Our results demonstrate that Sym-Q excels not only in recovering underlying mathematical structures but also uniquely learns to efficiently refine the output expression based on reward signals, thereby discovering…
• Zero-Shot Reinforcement Learning via Function Encoders
  30 Jan 2024 2 repositories listed Syntology ran 2 of 2 samples · 0 unverified · 2 pointer-only (licence)
  Although reinforcement learning (RL) can solve many challenging sequential decision making problems, achieving zero-shot transfer across related tasks remains a challenge.
• Adapting Static Fairness to Sequential Decision-Making: Bias Mitigation Strategies towards Equal Long-term Benefit Rate
  7 Sep 2023 2 repositories listed Syntology ran 0 of 1 samples · 1 unverified
  To address biases in sequential decision-making, we introduce a long-term fairness concept named Equal Long-term Benefit Rate (ELBERT).
• Learning Embeddings for Sequential Tasks Using Population of Agents
  5 Jun 2023 2 repositories listed
  We present an information-theoretic framework to learn fixed-dimensional embeddings for tasks in reinforcement learning.
• Trieste: Efficiently Exploring The Depths of Black-box Functions with TensorFlow
  16 Feb 2023 2 repositories listed Syntology ran 0 of 3 samples · 3 unverified
  We present Trieste, an open-source Python package for Bayesian optimization and active learning benefiting from the scalability and efficiency of TensorFlow.
• Temporal Latent Bottleneck: Synthesis of Fast and Slow Processing Mechanisms in Sequence Learning
  30 May 2022 2 repositories listed Syntology ran 0 of 1 samples · 1 unverified
  A slow stream that is recurrent in nature aims to learn a specialized and compressed representation, by forcing chunks of K time steps into a single representation which is divided into multiple vectors.
• Efficient Symptom Inquiring and Diagnosis via Adaptive Alignment of Reinforcement Learning and Classification
  1 Dec 2021 2 repositories listed
  To address this issue, we devise an adaptive mechanism to align reinforcement learning and classification methods using distribution entropy as the medium.
• Mixed Policy Gradient: off-policy reinforcement learning driven jointly by data and model
  23 Feb 2021 2 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  Formally, MPG is constructed as a weighted average of the data-driven and model-driven PGs, where the former is the derivative of the learned Q-value function, and the latter is that of the model-predictive return.
• Text-based RL Agents with Commonsense Knowledge: New Challenges, Environments and Baselines
  8 Oct 2020 2 repositories listed Syntology ran 0 of 13 samples · 13 unverified
  Text-based games have emerged as an important test-bed for Reinforcement Learning (RL) research, requiring RL agents to combine grounded language understanding with sequential decision making.
• PDDLGym: Gym Environments from PDDL Problems
  15 Feb 2020 2 repositories listed Syntology ran 0 of 11 samples · 11 unverified
  We present PDDLGym, a framework that automatically constructs OpenAI Gym environments from PDDL domains and problems.
• Policy Learning for Malaria Control
  20 Oct 2019 2 repositories listed
  In this report, we introduce the progress to learn the policy for Malaria Control as a Reinforcement Learning problem in the KDD Cup Challenge 2019 and propose diverse solutions to deal with the limited observations…
• Classification with Costly Features as a Sequential Decision-Making Problem
  5 Sep 2019 2 repositories listed Syntology ran 0 of 1 samples · 1 unverified
  This work focuses on a specific classification problem, where the information about a sample is not readily available, but has to be acquired for a cost, and there is a per-sample budget.
• SkipNet: Learning Dynamic Routing in Convolutional Networks
  26 Nov 2017 2 repositories listed
  While deeper convolutional networks are needed to achieve maximum accuracy in visual perception tasks, for many inputs shallower networks are sufficient.
• Detecting Adversarial Attacks on Neural Network Policies with Visual Foresight
  2 Oct 2017 2 repositories listed Syntology ran 0 of 10 samples · 10 unverified · 10 pointer-only (licence)
  Our core idea is that the adversarial examples targeting at a neural network-based policy are not effective for the frame prediction model.
• Learning model-based planning from scratch
  19 Jul 2017 2 repositories listed
  Here we introduce the "Imagination-based Planner", the first model-based, sequential decision-making agent that can learn to construct, evaluate, and execute plans.
• Doubly Robust Off-policy Value Evaluation for Reinforcement Learning
  11 Nov 2015 2 repositories listed
  We study the problem of off-policy value evaluation in reinforcement learning (RL), where one aims to estimate the value of a new policy based on data collected by a different policy.

Syntology lines on 15 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.