Reinforcement Learning |

Consent Chain Degradation in Embodied Multi-Agent Systems: Bridging the Gap Between AI Agent Governance and Robot Ethics

Mon, 01 Jun 2026 00:00:00 +0000

Introduces consent chain degradation: the way the specificity, validity and scope of human consent weaken as authority passes through chains of delegation among embodied agents. The paper proposes CoRVE, a three-layer runtime architecture for consent scope modelling, delegation tracking and physical irreversibility assessment, illustrates the problem with healthcare, domestic and industrial scenarios (including a worked numerical example), and maps the gaps left by the EU AI Act, the GDPR, the Machinery Regulation and the revised Product Liability Directive.

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When Does Adaptive Guidance Help? Belief-Aware Privileged Distillation for Autonomous Driving Under Partial Observability

Mon, 01 Jun 2026 00:00:00 +0000

Extends Guided Soft Actor-Critic with Belief-Aware GSAC, which scales the privileged-distillation coefficient by ensemble disagreement in a driving POMDP. Across three occlusion levels, adaptive guidance helps under mild and moderate occlusion; under severe occlusion the coefficient collapses to its minimum early (“observability blindness”) and a simple linear decay schedule performs best, suggesting that much of the benefit comes from scheduling rather than adaptivity.

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Workshop papers at ICRA 2026 and CVPR 2026

Mon, 01 Jun 2026 00:00:00 +0000

Two workshop papers appeared in June 2026:

, ICRA 2026 Workshop on Robot Ethics (WoRoBet), presented in Vienna. Preprint: .
, CVPR 2026 Workshop on Autonomous Driving (WAD). Preprint: .

Agent-Based Reinforcement Learning for Geochemical Control in Geothermal Energy Systems

Thu, 01 Jan 2026 00:00:00 +0000

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Bidirectional Human Interactive AI Framework for Social Robot Navigation

Mon, 13 May 2024 00:00:00 +0000

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Prediction of Lifted Weight Category Using EEG Equipped Headgear

Tue, 27 Sep 2022 00:00:00 +0000

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Cloud Assisted Connected and Automated Mobility System Architecture Design and Experimental Verification: The 5G-MOBIX Autonomous Truck Routing Use Case

Sun, 05 Jun 2022 00:00:00 +0000

Demonstrates the use of 5G networks for a cloud-assisted connected and automated mobility service in the EU H2020 5G-MOBIX project, with preliminary field tests of the autonomous truck routing use case at the Ford Otosan test track in Eskişehir, Türkiye.

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Autonomous Driving Systems for Decision-Making Under Uncertainty Using Deep Reinforcement Learning

Sun, 15 May 2022 00:00:00 +0000

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Deep Reinforcement Learning for Partially Observable Markov Decision Processes

Sat, 01 Jan 2022 00:00:00 +0000

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Guided Soft Actor Critic: A Guided Deep Reinforcement Learning Approach for Partially Observable Markov Decision Processes

Mon, 29 Nov 2021 00:00:00 +0000

Introduces Guided Soft Actor-Critic (GSAC), in which a guidance module steers Soft Actor-Critic during training to cope with partial observability, improving sample efficiency and final return on partially observable continuous-control tasks.

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Deep Reinforcement Learning for Simulation-Based Determination of COVID-19 Pandemic Mitigation Policies

Fri, 01 Jan 2021 00:00:00 +0000

A preliminary version was presented at the II. International Artificial Intelligence in Health Congress (SYZ 2021), İzmir.

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Modeling, simulation and fuzzy control of an anthropomorphic robot arm by using Dymola

Sun, 04 Jan 2009 00:00:00 +0000

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Modeling and Simulation of an Anthropomorphic Robot Arm by Using Dymola

Mon, 29 May 2006 00:00:00 +0000

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