Search results for "älykkäät agentit"
showing 8 items of 8 documents
How pedagogical agents communicate with students: A two-phase systematic review
2022
Technological advancements have improved the capabilities of pedagogical agents to communicate with students. However, an increased use of pedagogical agents in learning environments calls for a deeper understanding of student–agent communication to assess the effectiveness of pedagogical agents in learning. This study is a two-phase systematic review of scientific papers on pedagogical agent communication research published between 2010 and 2020, including review papers and original research papers. In the first phase, this study analyses literature reviews and meta-analyses to find the status and research gaps. The findings indicate that pedagogical agents' characteristics and impact on l…
Anthropomorphism and social presence in Human–Virtual service assistant interactions: The role of dialog length and attitudes
2022
In this study, we delve into the perceived quality of recommendations provided by AI-based virtual service assistants (VSAs). Specifically, the role of the social presence of VSAs in influencing recommendation perceptions is investigated. We also explore how the social presence of a VSA is formed and how perceived anthropomorphism plays a vital role in shaping social presence and eventually instilling trust in VSAs among consumers. These relationships are examined in the context of online government services. The results indicate that consumer interaction with VSAs - manifesting via perceived anthropomorphism, social presence, dialog length, and attitudes - improves recommendation quality p…
Dynamic aspects of industrial middleware architectures
2011
Data-driven Interactive Multiobjective Optimization : Challenges and a Generic Multi-agent Architecture
2020
In many decision making problems, a decision maker needs computer support in finding a good compromise between multiple conflicting objectives that need to be optimized simultaneously. Interactive multiobjective optimization methods have a lot of potential for solving such problems. However, the growth of complexity in problem formulations and the abundance of data bring new challenges to be addressed by decision makers and method developers. On the other hand, advances in the field of artificial intelligence provide opportunities in this respect. We identify challenges and propose directions of addressing them in interactive multiobjective optimization methods with the help of multiple int…
Agents driven smart sensors
2017
Any physical area (like schools, home, hospitals etc.) that uses either mobile devices, sensors, embedded systems or computers to gather information from the users and the environment and eventually, adapt according to the new information gained. [1] Smart spaces compromises of heterogeneous hardware which often leads to the issues of interoperability. One way of reducing the heterogeneity between the sensors is to introduce the semantic interface as sensors default interface. Semantic Web provides a common interface and for-mat for data representation so that one can decrease the heterogeneity of data and increase data reusability. [2] With the Smart Spaces, it is important to use only the…
Self-management in distributed systems : smart adaptive framework for pervasive computing environments
2013
Interacting with intelligent agents : key issues in agent-based decision support system design
2010
Explainable Fuzzy AI Challenge 2022 : Winner’s Approach to a Computationally Efficient and Explainable Solution
2022
An explainable artificial intelligence (XAI) agent is an autonomous agent that uses a fundamental XAI model at its core to perceive its environment and suggests actions to be performed. One of the significant challenges for these XAI agents is performing their operation efficiently, which is governed by the underlying inference and optimization system. Along similar lines, an Explainable Fuzzy AI Challenge (XFC 2022) competition was launched, whose principal objective was to develop a fully autonomous and optimized XAI algorithm that could play the Python arcade game “Asteroid Smasher”. This research first investigates inference models to implement an efficient (XAI) agent using rule-based …