35 citations · 53 across the 9 of their papers we have counts for
9 papers
GROSS: German Rail Open-Source SUMO Scenario
Juri Penell, Damian Dailisan
Microscopic simulation enables reproducible evaluation in intelligent transportation systems, yet most open SUMO scenarios and toolchains remain road-traffic centric, leaving rail…
Belief Engine: Configurable and Inspectable Stance Dynamics in Multi-Agent LLM Deliberation
Joshua C. Yang, Maurice Flechtner, Damian Dailisan +1
LLM-based agents are increasingly used to simulate deliberative interactions such as negotiation, conflict resolution, and multi-turn opinion exchange. Yet generated transcripts of…
Addressing Moral Uncertainty using Large Language Models for Ethical Decision-Making
Rohit K. Dubey, Damian Dailisan, Sachit Mahajan
We present an ethical decision-making framework that refines a pre-trained reinforcement learning (RL) model using a task-agnostic ethical layer. Following initial training, the RL…
Overcoming the Price of Anarchy by Steering with Recommendations
Cesare Carissimo, Marcin Korecki, Damian Dailisan
Varied real world systems such as transportation networks, supply chains and energy grids present coordination problems where many agents must learn to share resources. It is well…
LLM Voting: Human Choices and AI Collective Decision Making
Joshua C. Yang, Damian Dailisan, Marcin Korecki +2
This paper investigates the voting behaviors of Large Language Models (LLMs), specifically GPT-4 and LLaMA-2, their biases, and how they align with human voting patterns. Our metho…
Dynamic value alignment through preference aggregation of multiple objectives
Marcin Korecki, Damian Dailisan, Cesare Carissimo
The development of ethical AI systems is currently geared toward setting objective functions that align with human objectives. However, finding such functions remains a research ch…
Deep-learned orthogonal basis patterns for fast, noise-robust single-pixel imaging
Ritz Ann Aguilar, Damian Dailisan
Single-pixel imaging (SPI) is a novel, unconventional method that goes beyond the notion of traditional cameras but can be computationally expensive and slow for real-time applicat…
Adaptive Coordination Offsets for Signalized Arterial Intersections using Deep Reinforcement Learning
Keith Anshilo Diaz, Damian Dailisan, Umang Sharaf +5
Coordinating intersections in arterial networks is critical to the performance of urban transportation systems. Deep reinforcement learning (RL) has gained traction in traffic cont…
Crossover transitions in a bus-car mixed-traffic cellular automata model
Damian N. Dailisan, May T. Lim
We modify the Nagel-Schreckenberg (NaSch) cellular automata model to study mixed-traffic dynamics. We focus on the interplay between passenger availability and bus-stopping constra…