148 citations · 160 across the 17 of their papers we have counts for
8 papers · 1 filter
MACOptions: Multi-Agent Learning with Centralized Controller and Options Framework
Alakh Aggarwal, Rishita Bansal, Parth Padalkar +1
These days automation is being applied everywhere. In every environment, planning for the actions to be taken by the agents is an important aspect. In this paper, we plan to implem…
Dynamic probabilistic logic models for effective abstractions in RL
Harsha Kokel, Arjun Manoharan, Sriraam Natarajan +2
State abstraction enables sample-efficient learning and better task transfer in complex reinforcement learning environments. Recently, we proposed RePReL (Kokel et al. 2021), a hie…
A Preliminary Approach for Learning Relational Policies for the Management of Critically Ill Children
Michael A. Skinner, Lakshmi Raman, Neel Shah +2
The increased use of electronic health records has made possible the automated extraction of medical policies from patient records to aid in the development of clinical decision su…
User Friendly Automatic Construction of Background Knowledge: Mode Construction from ER Diagrams
Alexander L. Hayes, Mayukh Das, Phillip Odom +1
One of the key advantages of Inductive Logic Programming systems is the ability of the domain experts to provide background knowledge as modes that allow for efficient search throu…
Preference-Guided Planning: An Active Elicitation Approach
Mayukh Das, Phillip Odom, Md. Rakibul Islam +4
Planning with preferences has been employed extensively to quickly generate high-quality plans. However, it may be difficult for the human expert to supply this information without…
Application of Statistical Relational Learning to Hybrid Recommendation Systems
Shuo Yang, Mohammed Korayem, Khalifeh AlJadda +2
Recommendation systems usually involve exploiting the relations among known features and content that describe items (content-based filtering) or the overlap of similar users who i…
Learning Relational Dependency Networks for Relation Extraction
Dileep Viswanathan, Ameet Soni, Jude Shavlik +1
We consider the task of KBP slot filling -- extracting relation information from newswire documents for knowledge base construction. We present our pipeline, which employs Relation…
Counting Belief Propagation
Kristian Kersting, Babak Ahmadi, Sriraam Natarajan
A major benefit of graphical models is that most knowledge is captured in the model structure. Many models, however, produce inference problems with a lot of symmetries not reflect…