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05/26/2023
NASimEmu: Network Attack Simulator Emulator for Training Agents Generalizing to Novel Scenarios
Current frameworks for training offensive penetration testing agents wit...
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09/06/2022
Avast-CTU Public CAPE Dataset
There is a limited amount of publicly available data to support research...
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08/04/2022
Explaining Classifiers Trained on Raw Hierarchical Multiple-Instance Data
Learning from raw data input, thus limiting the need for feature enginee...
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12/23/2021
Continual Depth-limited Responses for Computing Counter-strategies in Extensive-form Games
In real-world applications, game-theoretic algorithms often interact wit...
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12/20/2021
Fast Algorithms for Poker Require Modelling it as a Sequential Bayesian Game
Many recent results in imperfect information games were only formulated ...
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10/22/2021
Improving Robustness of Malware Classifiers using Adversarial Strings Generated from Perturbed Latent Representations
In malware behavioral analysis, the list of accessed and created files v...
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05/19/2021
Mill.jl and JsonGrinder.jl: automated differentiable feature extraction for learning from raw JSON data
Learning from raw data input, thus limiting the need for manual feature ...
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02/27/2021
Multi-agent Reinforcement Learning in OpenSpiel: A Reproduction Report
In this report, we present results reproductions for several core algori...
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09/30/2020
Complexity and Algorithms for Exploiting Quantal Opponents in Large Two-Player Games
Solution concepts of traditional game theory assume entirely rational pl...
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09/25/2020
Symbolic Relational Deep Reinforcement Learning based on Graph Neural Networks
We present a novel deep reinforcement learning framework for solving rel...
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04/22/2020
Discovering Imperfectly Observable Adversarial Actions using Anomaly Detection
Anomaly detection is a method for discovering unusual and suspicious beh...
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11/20/2019
Deep Reinforcement Learning with Explicitly Represented Knowledge and Variable State and Action Spaces
We focus on a class of real-world domains, where gathering hierarchical ...
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09/05/2019
Classification with Costly Features as a Sequential Decision-Making Problem
This work focuses on a specific classification problem, where the inform...
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06/26/2019
Rethinking Formal Models of Partially Observable Multiagent Decision Making
Multiagent decision-making problems in partially observable environments...
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06/14/2019
Problems with the EFG formalism: a solution attempt using observations
We argue that the extensive-form game (EFG) model isn't powerful enough ...
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05/31/2019
Value Functions for Depth-Limited Solving in Zero-Sum Imperfect-Information Games
Depth-limited look-ahead search is an essential tool for agents playing ...
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12/18/2018
Monte Carlo Continual Resolving for Online Strategy Computation in Imperfect Information Games
Online game playing algorithms produce high-quality strategies with a fr...
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04/23/2018
Analysis of Hannan Consistent Selection for Monte Carlo Tree Search in Simultaneous Move Games
Hannan consistency, or no external regret, is a key concept for learning...
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03/14/2018
Constructing Imperfect Recall Abstractions to Solve Large Extensive-Form Games
Extensive-form games are an important model of finite sequential interac...
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11/20/2017
Classification with Costly Features using Deep Reinforcement Learning
We study a classification problem where each feature can be acquired for...
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01/06/2017
