Vincent KoemanVrije Universiteit Amsterdam | VU · Department of Computer Science
Vincent Koeman
Master of Science
About
18
Publications
3,117
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100
Citations
Citations since 2017
Introduction
Vincent Koeman currently works at the Department of Intelligent Systems, Delft University of Technology. Vincent does research in Software Engineering, Human-computer Interaction and Artificial Intelligence. His current project is 'Explaining the Behaviour of Cognitive Agents.'
Additional affiliations
December 2014 - March 2019
Publications
Publications (18)
Smart devices, such as smart phones, voice assistants and social robots, provide users with a range of input modalities, e.g., speech, touch, gestures, and vision. In recent years, advancements in processing of these input channels enable more natural interaction (e.g., automated speech, face, and gesture recognition, dialog generation, emotion exp...
Effective use of negotiation support systems depends on the systems capability of explaining itself to the user. This paper introduces the notion of an explanation matrix and an aberration detection mechanism for bidding strategies. The aberration detection is a mechanism that detects if one of the negotiating parties deviates from their expected b...
The issue of explainability for autonomous systems is becoming increasingly prominent. Several researchers and organisations have advocated the provision of a “Why did you do that?” button which allows a user to interrogate a robot about its choices and actions. We take previous work on debugging cognitive agent programs and apply it to the questio...
The evaluation of cognitive agent systems, which have been advocated as the next generation model for engineering complex, distributed systems, requires more benchmark environments that offer more features and involve controlling more units. One issue that needs to be addressed time and again is how to create a connector for interfacing cognitive a...
The continuous integration of software-intensive systems together with the ever-increasing computing power offer a breeding ground for intelligent agents and multi-agent systems (MAS) more than ever before. Over the past two decades, a wide variety of languages, models, techniques and methodologies have been proposed to engineer agents and MAS. Des...
It has been argued that the evaluation of cognitive agent systems requires richer benchmark problems. We think that real-time strategy (RTS) games can offer such a testbed, as AI for RTS requires the design of complicated strategies for coordinating hundreds of units that need to solve a range of challenges. Therefore, in this paper, we report on t...
See https://goalapl.atlassian.net/wiki/spaces/GOAL/pages/33043/Tutorials+Documentation+and+Education for the latest version.
![The 2APL agent decision cycle [9]](profile/Vincent-Koeman/publication/309515270/figure/fig5/AS:960468374007808@1606004913287/The-2APL-agent-decision-cycle-9_Q320.jpg)
When an agent program exhibits unexpected behaviour, a developer needs to locate the fault by debugging the agent’s source code. The process of fault localisation requires an understanding of how code relates to the observed agent behaviour. The main aim of this paper is to design a source-level debugger that supports single-step execution of a cog...
For real-time programs reproducing a bug by rerunning the system is likely to fail, making fault localization a time-consuming process. Omniscient debugging is a technique that stores each run in such a way that it supports going backwards in time. However, the overhead of existing omniscient debugging implementations for languages like Java is so...
The main goal of our demonstration is to show how omniscient debugging can be applied in practice to cognitive agents. A concrete implementation of the mechanisms proposed in Koeman et. al [2017] has been created for the GOAL agent programming language in the Eclipse environment, integrated with the source-level debugger of Koeman et. al [2016], th...
Debugging is notoriously difficult and extremely time consuming but also essential for ensuring the reliability and quality of a software system. In order to reduce debugging effort and enable automated failure detection, we propose an automated testing framework for detecting failures in cognitive agent programs. Our approach is based on the assum...
In order to reduce debugging effort and enable automated failure detection, we proposed an automated testing framework for cognitive agent programs that provides support for detecting frequently occurring failure types. Automated testing yields a reduction in the effort needed to detect a failure and is more effective than manual code inspection me...
![Fig. 1. The structure and decision cycle of a Goal agent [8].](profile/Vincent-Koeman/publication/321384376/figure/fig1/AS:566358782824453@1512041864762/The-structure-and-decision-cycle-of-a-Goal-agent-8_Q320.jpg)
![Table 2 . Information sources for testing [17].](profile/Vincent-Koeman/publication/321384376/figure/tbl1/AS:670418063085579@1536851530651/Information-sources-for-testing-17_Q320.jpg)
In order to reduce debugging effort and enable automated failure detection, we proposed an automated testing framework for detecting failures in cognitive agent programs in previous work. This approach is based on a minimal set of temporal operators that enable the specification of test conditions with sufficient expressiveness for detecting all fa...
When an agent program exhibits unexpected behaviour, a developer needs to locate the fault by debugging the agent’s source code. The process of fault localisation requires an understanding of how code relates to the observed agent behaviour. The main aim of this paper is to design a source-level debugger that supports single-step execution of a cog...
When provided with the support of proper development and maintenance tools, programmers are more likely to work efficiently and produce high-quality software. A mature and professional Integrated Development Environment (IDE) provides the required tools in an integrated manner and allows those tools to be easily adapted for use in new contexts as w...
We describe the process of designing and implementing the Fawkes Agent, the winner of the ANAC 2013 automated negotiation competition. The competition is performed using the GENIUS negotiation platform. The agent needs an acceptance strategy, a bidding strategy, an opponent model and a concession strategy.
Projects
Projects (2)
Agents that can explain their choice of action are useful not only for end users, but also for the developers of such agents. An agent developer needs to identify defects in the agent programs (s)he writes. Debugging an agent program requires analysing the behaviour generated by a cognitive agent program that is unexpected or undesired. In order to understand how this behaviour is generated, it would be of great value to a programmer if an agent can explain why it chose to do something it did. In order to set a clear scope for our work, we will focus on explanations aimed at agent developers. We believe that an explanation facility for developers is a step towards an explanation facility for end-users of applications built using cognitive agents.
