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In a Nutshell, the Human Asked for This: Latent Goals for Following
  Temporal Specifications

In a Nutshell, the Human Asked for This: Latent Goals for Following Temporal Specifications

18 October 2021
Borja G. Leon
Murray Shanahan
Francesco Belardinelli
    AI4CE
ArXivPDFHTML

Papers citing "In a Nutshell, the Human Asked for This: Latent Goals for Following Temporal Specifications"

12 / 12 papers shown
Title
Skill Expansion and Composition in Parameter Space
Skill Expansion and Composition in Parameter Space
Tenglong Liu
J. Li
Yinan Zheng
Haoyi Niu
Yixing Lan
Xin Xu
Xianyuan Zhan
58
4
0
09 Feb 2025
BlendRL: A Framework for Merging Symbolic and Neural Policy Learning
BlendRL: A Framework for Merging Symbolic and Neural Policy Learning
Hikaru Shindo
Quentin Delfosse
D. Dhami
Kristian Kersting
41
3
0
15 Oct 2024
Generalization of Compositional Tasks with Logical Specification via
  Implicit Planning
Generalization of Compositional Tasks with Logical Specification via Implicit Planning
Duo Xu
Faramarz Fekri
OffRL
23
1
0
13 Oct 2024
DeepLTL: Learning to Efficiently Satisfy Complex LTL Specifications for Multi-Task RL
DeepLTL: Learning to Efficiently Satisfy Complex LTL Specifications for Multi-Task RL
Mathias Jackermeier
Alessandro Abate
OffRL
40
1
0
06 Oct 2024
Reward Machines for Deep RL in Noisy and Uncertain Environments
Reward Machines for Deep RL in Noisy and Uncertain Environments
Andrew C. Li
Zizhao Chen
Toryn Q. Klassen
Pashootan Vaezipoor
Rodrigo Toro Icarte
Sheila A. McIlraith
48
6
0
31 May 2024
LTL-Constrained Policy Optimization with Cycle Experience Replay
LTL-Constrained Policy Optimization with Cycle Experience Replay
Ameesh Shah
Cameron Voloshin
Chenxi Yang
Abhinav Verma
Swarat Chaudhuri
S. Seshia
29
1
0
17 Apr 2024
Reinforcement Learning with Knowledge Representation and Reasoning: A Brief Survey
Reinforcement Learning with Knowledge Representation and Reasoning: A Brief Survey
Chao Yu
Xuejing Zheng
H. Zhuo
OffRL
LRM
55
7
0
24 Apr 2023
Generalizing LTL Instructions via Future Dependent Options
Generalizing LTL Instructions via Future Dependent Options
Duo Xu
Faramarz Fekri
OffRL
AI4CE
24
1
0
08 Dec 2022
Noisy Symbolic Abstractions for Deep RL: A case study with Reward
  Machines
Noisy Symbolic Abstractions for Deep RL: A case study with Reward Machines
Andrew C. Li
Zizhao Chen
Pashootan Vaezipoor
Toryn Q. Klassen
Rodrigo Toro Icarte
Sheila A. McIlraith
OffRL
10
9
0
20 Nov 2022
Categorical semantics of compositional reinforcement learning
Categorical semantics of compositional reinforcement learning
Georgios Bakirtzis
M. Savvas
Ufuk Topcu
CoGe
38
4
0
29 Aug 2022
LTL2Action: Generalizing LTL Instructions for Multi-Task RL
LTL2Action: Generalizing LTL Instructions for Multi-Task RL
Pashootan Vaezipoor
Andrew C. Li
Rodrigo Toro Icarte
Sheila A. McIlraith
OffRL
AI4CE
42
73
0
13 Feb 2021
Multi-Agent Reinforcement Learning with Temporal Logic Specifications
Multi-Agent Reinforcement Learning with Temporal Logic Specifications
Lewis Hammond
Alessandro Abate
Julian Gutierrez
Michael Wooldridge
AI4CE
42
32
0
01 Feb 2021
1