Kale-ab Abebe Tessera

According to our database, Kale-ab Abebe Tessera authored at least 15 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

CODA: Coordination via On-Policy Diffusion for Multi-Agent Offline Reinforcement Learning.

Marcel Hedman, Kale-ab Abebe Tessera, Juan Claude Formanek, Anya Sims, Riccardo Zamboni, Trevor McInroe, John Torr, Elliot Fosong

CoRR, April, 2026

Probing Dec-POMDP Reasoning in Cooperative MARL.

Kale-ab Abebe Tessera, Leonard Hinckeldey, Riccardo Zamboni, David Abel, Amos J. Storkey

CoRR, February, 2026

Fairness over Equality: Correcting Social Incentives in Asymmetric Sequential Social Dilemmas.

Alper Demir, Hüseyin Aydin, Kale-ab Abebe Tessera, David Abel, Stefano V. Albrecht

CoRR, February, 2026

2025

Remembering the Markov Property in Cooperative MARL.

Kale-ab Abebe Tessera, Leonard Hinckeldey, Riccardo Zamboni, David Abel, Amos Storkey

CoRR, July, 2025

TAR²: Temporal-Agent Reward Redistribution for Optimal Policy Preservation in Multi-Agent Reinforcement Learning.

Aditya Kapoor, Kale-ab Abebe Tessera, Mayank Baranwal, Harshad Khadilkar, Stefano V. Albrecht, Limin Sun

CoRR, February, 2025

HyperMARL: Adaptive Hypernetworks for Multi-Agent RL.

Kale-ab Abebe Tessera, Arrasy Rahman, Amos J. Storkey, Stefano V. Albrecht

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

2024

Agent-Temporal Credit Assignment for Optimal Policy Preservation in Sparse Multi-Agent Reinforcement Learning.

Aditya Kapoor, Sushant Swamy, Kale-ab Abebe Tessera, Mayank Baranwal, Mingfei Sun, Harshad Khadilkar, Stefano V. Albrecht

CoRR, 2024

HyperMARL: Adaptive Hypernetworks for Multi-Agent RL.

Kale-ab Abebe Tessera, Arrasy Rahman, Stefano V. Albrecht

CoRR, 2024

2023

Efficiently Quantifying Individual Agent Importance in Cooperative MARL.

Omayma Mahjoub, Ruan de Kock, Siddarth Singh, Wiem Khlifi, Abidine Vall, Kale-ab Abebe Tessera, Arnu Pretorius

CoRR, 2023

How much can change in a year? Revisiting Evaluation in Multi-Agent Reinforcement Learning.

Siddarth Singh, Omayma Mahjoub, Ruan de Kock, Wiem Khlifi, Abidine Vall, Kale-ab Abebe Tessera, Arnu Pretorius

CoRR, 2023

Generalisable Agents for Neural Network Optimisation.

Kale-ab Abebe Tessera, Callum Rhys Tilbury, Sasha Abramowitz, Ruan de Kock, Omayma Mahjoub, Benjamin Rosman, Sara Hooker, Arnu Pretorius

CoRR, 2023

Are we going MAD? Benchmarking Multi-Agent Debate between Language Models for Medical Q&A.

Andries P. Smit, Paul Duckworth, Nathan Grinsztajn, Kale-ab Abebe Tessera, Thomas D. Barrett, Arnu Pretorius

CoRR, 2023

Selective Reincarnation: Offline-to-Online Multi-Agent Reinforcement Learning.

Claude Formanek, Callum Rhys Tilbury, Jonathan Shock, Kale-ab Abebe Tessera, Arnu Pretorius

CoRR, 2023

2021

On pseudo-absence generation and machine learning for locust breeding ground prediction in Africa.

Ibrahim Salihu Yusuf, Kale-ab Abebe Tessera, Thomas Tumiel, Sella Nevo, Arnu Pretorius

CoRR, 2021

Keep the Gradients Flowing: Using Gradient Flow to Study Sparse Network Optimization.

Kale-ab Abebe Tessera, Sara Hooker, Benjamin Rosman

CoRR, 2021