This special issue of Artificial Life presents some of the finest papers from the Conference on Artificial Life (ALIFE 2022), which took place online from July 19 to 22, 2022. The conference was streamed from the University of Trento because of the ongoing COVID-19 pandemic. It was a wonderful event with approximately 300 participants and a busy program that offered eight keynote talks; nine hours of special sessions; and 52 hours of workshops, tutorials, and talks in parallel sessions.
The ALIFE 2022 conference theme was “La DOLCE Vita: Discoveries on Life Complexity and Evolution for the Improvement of Real Lives.” The conference theme explores how to improve the quality of real life using techniques and discoveries from the ALife field (see Figure 1). This covers various topics, including (but not limited to) the creation of artificial cells and organisms for health and technological applications; engineered ecosystems for improved environmental quality and sustainable agriculture; virtual/augmented reality creations with positive social impact; the well-being of our digital infrastructure; artificial intelligence (AI) and ALife algorithms for equitable access to resources and accurate information; AI, ALife, or robot assistance for those in need; AI, ALife, or robot applications for food production and distribution; the regeneration, redistribution, and reuse of everyday resources; microbial fuel cell systems for renewable energy; and other innovative technologies for social good.
The ALIFE 2022 conference attracted a total of 129 submissions, and all of them were reviewed by three reviewers. Senior program committee members then performed a topic-wide meta-review to arrive at acceptance decisions. The review process was double blind. Seventy-eight submissions were accepted and published in the open-access conference proceedings available from the MIT Press website (Holler et al., 2022). The authors of the finest papers were invited to submit extended versions of their conference manuscripts, which went through an additional two rounds of peer review and revision. As a result, five articles are included in this special issue:
Witkowski and Schwitzgebel, “The Ethics of Life as It Could Be: Do We Have Moral Obligations to Artificial Life?” The Artificial Life field explores the living state through modeling and the artificial creation of living systems. Under specific conditions, these systems might warrant moral consideration akin to animals or humans. Witowski et al. explore questions of the moral status of “technologically designed entities from the perspective of Artificial Life research.” “If Artificial Life is larger than life, then the ethics of artificial beings should be larger than human ethics.”
Merritt et al., “The Dynamics of Social Interaction Among Evolved Model Agents.” Merritt et al. revisit perceptual crossing simulation studies, evolving the systems further and accentuating the importance of dynamical and nonclonal analysis for models of social interaction. They also emphasize the opportunities for dialogue between artificial and human perceptual crossing studies and highlight the contributions of simulation studies to better understanding social interactions.
Pigozzi, “Pressure-Based Soft Agents.” Biological agents have bodies that comprise mostly soft tissue. Pigozzi proposes a novel soft-bodied agent formalism, namely, pressure-based soft agents (PSAs). His results suggest that PSAs are effective at various tasks and emphasize PSAs’ importance in modeling soft-bodied agents.
Hodjat et al., “Domain-Independent Lifelong Problem Solving Through Distributed ALife Actors.” Hodjat et al. create a domain-independent problem-solving system based on the principles of Artificial Life. In this system, DIAS are the input and output dimensions. DIAS was shown to be able to solve problems with different dimensionality and complexity better than a standard noncollective approach. “DIAS therefore demonstrates a role for ALife in building scalable, general, and adaptive problem-solving systems.”
Matsumura et al., “Active Inference With Empathy Mechanism for Socially Behaved Artificial Agents in Diverse Situations.” Matsumura et al. propose an innovative method for an artificial agent to behave in a social manner. Results show that agents using this method exhibit more adaptive social behavior compared to those using standard active inference. Additionally, the study observes that the method prompted more social behavior with altruistic peers but less so with selfish ones.