Christopher Geib

1.9k total citations
51 papers, 1.2k citations indexed

About

Christopher Geib is a scholar working on Artificial Intelligence, Computer Networks and Communications and Computer Vision and Pattern Recognition. According to data from OpenAlex, Christopher Geib has authored 51 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Artificial Intelligence, 14 papers in Computer Networks and Communications and 9 papers in Computer Vision and Pattern Recognition. Recurrent topics in Christopher Geib's work include AI-based Problem Solving and Planning (28 papers), Logic, Reasoning, and Knowledge (11 papers) and Constraint Satisfaction and Optimization (11 papers). Christopher Geib is often cited by papers focused on AI-based Problem Solving and Planning (28 papers), Logic, Reasoning, and Knowledge (11 papers) and Constraint Satisfaction and Optimization (11 papers). Christopher Geib collaborates with scholars based in United States, United Kingdom and Slovenia. Christopher Geib's co-authors include Robert P. Goldman, Mark Steedman, Aleš Ude, Danica Kragić, Volker Krüger, Ronald P. A. Petrick, Gita Sukthankar, David V. Pynadath, Hung Bui and Norbert Krüger and has published in prestigious journals such as Artificial Intelligence, Robotics and Autonomous Systems and AI Magazine.

In The Last Decade

Christopher Geib

50 papers receiving 1.1k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Christopher Geib	762	390	291	227	104	51	1.2k
Karen Zita Haigh	512 0.7×	405 1.0×	122 0.4×	214 0.9×	64 0.6×	48	976
R. James Firby	925 1.2×	512 1.3×	291 1.0×	268 1.2×	79 0.8×	35	1.4k
Gita Sukthankar	602 0.8×	264 0.7×	76 0.3×	130 0.6×	62 0.6×	113	1.1k
Ronald P. A. Petrick	906 1.2×	362 0.9×	353 1.2×	91 0.4×	229 2.2×	81	1.4k
Federico Pecora	523 0.7×	440 1.1×	245 0.8×	304 1.3×	269 2.6×	96	1.1k
Slim Abdennadher	584 0.8×	119 0.3×	88 0.3×	315 1.4×	67 0.6×	113	1.1k
Yuri Ivanov	652 0.9×	1.2k 3.1×	238 0.8×	86 0.4×	126 1.2×	49	1.7k
Joyce Chai	1.3k 1.7×	575 1.5×	161 0.6×	91 0.4×	158 1.5×	125	1.9k
Vicente Matellán Olivera	217 0.3×	217 0.6×	110 0.4×	134 0.6×	104 1.0×	114	805
G. Michael Youngblood	301 0.4×	508 1.3×	62 0.2×	253 1.1×	33 0.3×	46	920

Countries citing papers authored by Christopher Geib

Since Specialization

Citations

This map shows the geographic impact of Christopher Geib's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Christopher Geib with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christopher Geib more than expected).

Fields of papers citing papers by Christopher Geib

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Christopher Geib. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Christopher Geib. The network helps show where Christopher Geib may publish in the future.

Co-authorship network of co-authors of Christopher Geib

This figure shows the co-authorship network connecting the top 25 collaborators of Christopher Geib. A scholar is included among the top collaborators of Christopher Geib based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Christopher Geib. Christopher Geib is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Ontañón, Santiago, et al.. (2019). Extracting CCGs for Plan Recognition in RTS Games.. National Conference on Artificial Intelligence. 9–16. 4 indexed citations

Geib, Christopher. (2017). Partial Observability in Grammar Based Plan Recognition.. National Conference on Artificial Intelligence. 1 indexed citations

Geib, Christopher, et al.. (2016). Building Helpful Virtual Agents Using Plan Recognition and Planning. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 12(1). 162–168. 4 indexed citations

Sukthankar, Gita, Christopher Geib, Hung Bui, David V. Pynadath, & Robert P. Goldman. (2014). Plan, Activity, and Intent Recognition: Theory and Practice. Journal of International Crisis and Risk Communication Research. 424–424. 108 indexed citations

Geib, Christopher, et al.. (2013). Parallelizing plan recognition. National Conference on Artificial Intelligence. 10–16. 1 indexed citations

Geib, Christopher & Robert P. Goldman. (2010). Handling looping and optional actions in YAPPR. National Conference on Artificial Intelligence. 17–22. 1 indexed citations

Geib, Christopher. (2009). Delaying commitment in plan recognition using combinatory categorial grammars. International Joint Conference on Artificial Intelligence. 1702–1707. 25 indexed citations

Krüger, Norbert, Justus Piater, Florentin Wörgötter, et al.. (2009). A Formal Definition of Object-Action Complexes and Examples at Different Levels of the Processing Hierarchy. Computer and Information Science. 83(8). 1–39. 20 indexed citations

Geib, Christopher & Robert P. Goldman. (2009). A probabilistic plan recognition algorithm based on plan tree grammars. Artificial Intelligence. 173(11). 1101–1132. 130 indexed citations

10.

Geib, Christopher, John Maraist, & Robert P. Goldman. (2008). A new probabilistic plan recognition algorithm based on string rewriting. International Conference on Automated Planning and Scheduling. 91–98. 22 indexed citations

11.

Geib, Christopher & Mark Steedman. (2007). On natural language processing and plan recognition. International Joint Conference on Artificial Intelligence. 1612–1617. 34 indexed citations

12.

Haigh, Karen Zita, et al.. (2004). The independent lifestyle assistant™ (I.L.S.A.): AI lessons learned. Innovative Applications of Artificial Intelligence. 852–857. 33 indexed citations

13.

Haigh, Karen Zita, et al.. (2004). The Independent LifeStyle Assistant TM (I.L.S.A.): AI Lessons Learned.. National Conference on Artificial Intelligence. 852–857. 3 indexed citations

14.

Geib, Christopher. (2004). Assessing the complexity of plan recognition. National Conference on Artificial Intelligence. 507–512. 24 indexed citations

15.

Geib, Christopher & Robert P. Goldman. (2003). Recognizing plan/goal abandonment. International Joint Conference on Artificial Intelligence. 1515–1517. 22 indexed citations

16.

Geib, Christopher & Robert P. Goldman. (2001). Probabilistic Plan Recognition for Hostile Agents. The Florida AI Research Society. 580–584. 22 indexed citations

17.

Boutilier, Craig, Ronen I. Brafman, & Christopher Geib. (1997). Prioritized goal decomposition of Markov decision processes: toward a synthesis of classical and decision theoretic planning. International Joint Conference on Artificial Intelligence. 1156–1162. 33 indexed citations

18.

Badler, Norman I., Bonnie Webber, Matthew Stone, et al.. (1996). Planning for animation. Scholarly Commons (University of Pennsylvania). 235–262. 16 indexed citations

19.

Geib, Christopher. (1994). The Intentional planning system: ItPlanS. ScholarlyCommons (University of Pennsylvania). 55–60. 18 indexed citations

20.

Geib, Christopher & Bonnie Webber. (1993). A Consequence of Incorporating Intentions in Means-end Planning. 9 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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