# Artificial Empathy and Imprecise Communication in a Multi-Agent System
## 3 Proposed Model  
The concept of artificial empathy is derived from analyzing the cooperative dynamics observed in human collective behaviors and identified as general empathy. This analysis focuses on identifying the requisite knowledge and experiential parameters that enable humans to execute effective behavioral strategies. Central to this concept is the role of uncertainty inherent in the model. When considering human cooperation, an easy observation is the enhancement of collaborative efficacy through the adoption of another individual's perspective. This process, essentially an embodiment of cognitive empathy, involves understanding and internalizing the mental state of another agent. Cognitive empathy, in this framework, is defined as the capability to comprehend the state of another agent, and subsequently, utilize this understanding to predict environmental conditions and the behaviors of the target entity. This predictive model, however, is subject to various uncertainties. These uncertainties primarily stem from the inherent complexity and variability of the agents' internal states and environmental conditions. Additionally, the model faces challenges due to imperfect communication, particularly in terms of the medium used for interaction. The quality and reliability of communication channels can significantly impact the accuracy and effectiveness of the transmitted information, adding another layer of uncertainty to the model. The newly formulated model of artificial empathy in swarm behavior is influenced by human decision-making mechanisms in cooperative tasks. In such situations, individuals accumulate knowledge and experiences, which inform their decision-making process. When collaborating, they not only rely on their knowledge but also consider the experiences and knowledge of others. However, direct access to another person's cognitive processes is not feasible. Instead, interactions are mediated through the interpretation of signals and messages from fellow participants, with a significant portion of these signals encompassing emotional information [1]. Upon receiving such signals, a decision maker must infer the knowledge state that these signals represent, including possible consequences [20]. This involves mentally reconstructing the sender's knowledge state, using the receiver's cognitive framework as a reference. The decision-making process then entails an integration of this inferred state with the individual's knowledge and capabilities. The critical decision lies in choosing whether to act based on personal goals and skills or to join efforts with others to enhance collective performance. This model, thus, reflects the complexities inherent in human-like decision making within the context of (fuzzy) multi-agent systems and artificial swarm behavior, underscoring the significance of empathetic understanding in cooperative dynamics. The following subsections of this paper formally define behavior in a setting where a finite number of agents (a swarm) collaborate towards a common goal. This model extends on a simple decision scheme given in [21] by adding the cognitive and emotional state, providing uncertainty handling and precise definition of goal operator. The overview of the proposed model is given in Figure 1. The general idea of the this solution is that, in each iteration, the agent evaluates the current situation and selects an action to perform from the following options: executing its own action, assisting other agents, or learning from others. By applying cognitive empathy, this decision is made not only based on the agent's independent assessment of its own situation but also on its perception of the state of others. When the agent makes a egoistic decision, it optimizes its own (local) reward, whereas by exhibiting empathetic behavior (assisting others), it has the potential to contribute to achieving a better global state. After each performed action, the outcome is evaluated, and, if necessary, the knowledge base is updated.