Creating and Capturing Artificial Emotions in Autonomous Robots and Software Agents

This paper presents ARTEMIS, a control system for autonomous robots or software agents. ARTEMIS can create human-like artificial emotions during interactions with their environment. We describe the underlying mechanisms for this. The control system also captures its past artificial emotions. A specific interpretation of a knowledge graph, called an Agent Knowledge Graph, stores these artificial emotions. ARTEMIS then utilizes current and stored emotions to adapt decision making and planning processes. As proof of concept, we realize a concrete software agent based on the ARTEMIS control system. This software agent acts as a user assistant and executes their orders and instructions. The environment of this user assistant consists of several other autonomous agents that offer their services. The execution of a user’s orders requires interactions of the user assistant with these autonomous service agents. These interactions lead to the creation of artificial emotions within the user assistant. The first experiments show that it is possible to realize an autonomous user assistant with plausible artificial emotions with ARTEMIS and record these artificial emotions in its Agent Knowledge Graph. The results also show that captured emotions support successful planning and decision making in complex dynamic environments. The user assistant with emotions surpasses an emotionless version of the user assistant.

Possessing reasons: why the awareness-first approach is better than the knowledge-first approach

In order for a reason to justify an action or attitude it must be one that is possessed by an agent. Knowledge-centric views of possession ground our possession of reasons, at least partially, either in our knowledge of them or in our being in a position to know them. On virtually all accounts, knowing P is some kind of non-accidental true belief that P. This entails that knowing P is a kind of non-accidental true representation that P. I outline a novel theory of the epistemic requirement on possession in terms of this more general state of non-accidental true representation. It is just as well placed to explain the motivations behind knowledge-centric views of possession, and it is also better placed to explain the extent of the reasons we possess in certain cases of deductive belief-updates and cases involving environmental luck. I conclude with three reflections. First, I indicate how my arguments generate a dilemma for Errol Lord’s (2018a) view that possessing reasons is just a matter of being in a position to manifest one’s knowledge how to use them. Second, I explain how my view can simultaneously manage cases of environmental luck without falling prey to lottery cases. Finally, I sketch the direction for a further range of counterexamples to knowledge-centric theories of possession.

Recapitulation of brand anthropomorphism: An innovating marketing strategy

The aim of this paper is to explain anthropomorphic marketing by illustrating the factors associated with the sociality motivation , effectance motivation, and elicited agent knowledge model (SEEK). This model was designed to explain anthropomorphic tendencies of a brand, as we do not know much about why people view non-human entities as human-like. In addition, this paper also focuses on how anthropomorphic representation strategies are used by marketers in the present scenario to build strong consumer-brand relationships and how these anthropomorphic marketing strategies affect the consumer-brand evaluation process. This paper examines the anthropomorphism of the brand by examining in depth the factors related to the SEEK model and explaining the anthropomorphic patterns of the market. It shows how consumers or advertisers view, imagine, interpret and exploit a non-human entity. Consumers can evaluate an anthropomorphic marketing strategy either positively or negatively. Therefore, marketers should use this tendency to anthropomorphise any brand or a product carefully. This literature review has important implications and it provides direction for researchers, as well as advanced investigation of brand anthropomorphism.

A developed software agent-knowledge-assisted procurement management tool for retailing enterprise

PurposeThis study aims to develop a software agent-knowledge procurement management tool to address uncertainties from external and internal environments, such as record failure, slow logistics auditing and distribution delay toward improving procurement management in retailing enterprises.Design/methodology/approachQuantitative methodology was used to collect data using a self-administered survey from randomly selected procurement staffs, marketers and customers to measure their perception regarding the feasibility and acceptance of the implemented agent-knowledge-based procurement management tool.FindingsResults from empirical analysis reveal that the implemented tool facilitates collaboration and interaction among buyers, sellers and procurement managers toward enhancing procurement managers’ flexibility to handle unexpected exceptions. In addition, results confirm the feasibility of the implemented tool in supporting procurement management toward handling inventory failure exception, which occurs in traditional procurement approaches. Moreover, descriptive results from user acceptance test verify that the tool was accepted by the respondents.Research limitations/implicationsThe limitation of this study is that the implemented tool is evaluated using data collected from respondents in Malaysia retailing enterprise only; thus, the results cannot be generalized to other enterprises and country. In addition, research implications from this study design a methodological and comprehensive software agent-knowledge-based model that support buyers, sellers and procurement managers with information to facilitate buying and selling operations.Practical implicationsPractically, the designed software agent-knowledge-based model describes how software agents collaborate with each other to facilitate procurement tasks and also use the knowledge base in the implemented tool to provide information sharing platform that manages the dynamics of procurement operations.Social implicationsThis research integrates software agents which are autonomous programs that carryout pre-defined task on behalf of end users. Socially, this study would be useful for procurement managers in developing mechanisms for instilling insights in retailing operations.Originality/valueThis research is among the first to attempt to develop a software agent-knowledge-based model to support procurement management in the retailing enterprise domain. It contributes to promote e-procurement practices by implementing a software agent-knowledge-oriented tool to address uncertainties experienced in retailing enterprise. It is envisaged that this study will provide basis for future research into e-procurement practices for retailing businesses in Malaysia and beyond.