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Learning, Planning, and Control in a Monolithic Neural Event Inference
  Architecture
v1v2 (latest)

Learning, Planning, and Control in a Monolithic Neural Event Inference Architecture

19 September 2018
Martin Volker Butz
D. Bilkey
Dania Humaidan
A. Knott
S. Otte
    AI4TS
ArXiv (abs)PDFHTML

Papers citing "Learning, Planning, and Control in a Monolithic Neural Event Inference Architecture"

13 / 13 papers shown
Flexible task abstractions emerge in linear networks with fast and bounded units
Flexible task abstractions emerge in linear networks with fast and bounded unitsNeural Information Processing Systems (NeurIPS), 2024
Kai Sandbrink
Jan P. Bauer
A. Proca
Andrew M. Saxe
Christopher Summerfield
Ali Hummos
483
4
0
17 Jan 2025
A Review of Mechanistic Models of Event Comprehension
A Review of Mechanistic Models of Event Comprehension
Tan T. Nguyen
183
0
0
17 Sep 2024
Gradient-based inference of abstract task representations for
  generalization in neural networks
Gradient-based inference of abstract task representations for generalization in neural networks
Ali Hummos
Felipe del-Rio
Brabeeba Mien Wang
Julio Hurtado
Cristian B. Calderon
G. Yang
279
4
0
24 Jul 2024
Binding Dancers Into Attractors
Binding Dancers Into AttractorsInternational Conference on Development and Learning (ICDL), 2022
Franziska Kaltenberger
S. Otte
Martin Volker Butz
127
2
0
01 Jun 2022
Inference of Affordances and Active Motor Control in Simulated Agents
Inference of Affordances and Active Motor Control in Simulated AgentsFrontiers in Neurorobotics (Front. Neurorobot.), 2022
Fedor Scholz
Christian Gumbsch
S. Otte
Martin Volker Butz
AI4CE
321
7
0
23 Feb 2022
Goal-directed Planning and Goal Understanding by Active Inference:
  Evaluation Through Simulated and Physical Robot Experiments
Goal-directed Planning and Goal Understanding by Active Inference: Evaluation Through Simulated and Physical Robot Experiments
Takazumi Matsumoto
Wataru Ohata
Fabien C. Y. Benureau
Jun Tani
155
13
0
21 Feb 2022
Branching Time Active Inference: empirical study and complexity class
  analysis
Branching Time Active Inference: empirical study and complexity class analysisNeural Networks (NN), 2021
Théophile Champion
Howard L. Bowman
Marek Grze's
AI4CE
258
15
0
22 Nov 2021
Sparsely Changing Latent States for Prediction and Planning in Partially
  Observable Domains
Sparsely Changing Latent States for Prediction and Planning in Partially Observable DomainsNeural Information Processing Systems (NeurIPS), 2021
Christian Gumbsch
Martin Volker Butz
Georg Martius
AI4CE
347
26
0
29 Oct 2021
Binding and Perspective Taking as Inference in a Generative Neural
  Network Model
Binding and Perspective Taking as Inference in a Generative Neural Network ModelInternational Conference on Artificial Neural Networks (ICANN), 2020
Mahdi Sadeghi
Fabian Schrodt
S. Otte
Martin Volker Butz
183
2
0
09 Dec 2020
Active Tuning
Active Tuning
S. Otte
Matthias Karlbauer
Martin Volker Butz
AI4TS
171
7
0
02 Oct 2020
Latent State Inference in a Spatiotemporal Generative Model
Latent State Inference in a Spatiotemporal Generative ModelInternational Conference on Artificial Neural Networks (ICANN), 2020
Matthias Karlbauer
Tobias Menge
S. Otte
Hendrik P. A. Lensch
Thomas Scholten
V. Wulfmeyer
Martin Volker Butz
151
1
0
21 Sep 2020
Goal-Directed Planning for Habituated Agents by Active Inference Using a
  Variational Recurrent Neural Network
Goal-Directed Planning for Habituated Agents by Active Inference Using a Variational Recurrent Neural NetworkEntropy (Entropy), 2020
Takazumi Matsumoto
Jun Tani
DRL
246
32
0
27 May 2020
Fostering Event Compression using Gated Surprise
Fostering Event Compression using Gated Surprise
Dania Humaidan
S. Otte
Martin Volker Butz
106
4
0
12 May 2020
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