Mustafa Devrim Kaba — accepted AI-conference papers

2025

Automated Composition of Agents: A Knapsack Approach for Agentic Component Selection

Michelle Yuan, Khushbu Pahwa, Shuaichen Chang, Mustafa Devrim Kaba, MONICA SUNKARA, Jiarong Jiang +2

NeurIPS 2025poster

Designing effective agentic systems requires the seamless composition and integration of agents, tools, and models within dynamic and uncertain environments. Most existing methods rely on static, semantic retrieval approaches for tool or agent discovery. However, effective reuse and composition of e…

Cited by 0 Source ↗Scholar ↗

2017

A Reinforcement Learning Approach to the View Planning Problem

Mustafa Devrim Kaba, Mustafa Gokhan Uzunbas, Ser Nam Lim

CVPR 2017poster

We present a Reinforcement Learning (RL) solution to the view planning problem (VPP), which generates a sequence of view points that are capable of sensing all accessible area of a given object represented as a 3D model. In doing so, the goal is to minimize the number of view points, making the VPP…

Cited by 68 PDF ↗Scholar ↗