IEEE Computational Intelligence Magazine - May 2022 - 12

Critical Thinking About Explainable AI
(XAI) for Rule-Based Fuzzy Systems,
by J. M. Mendel and P.P. Bonissone,
IEEE Transactions on Fuzzy Systems,
Vol. 29, No. 12, December 2021,
pp. 3579-3593.
Digital Object Identifier: 10.1109/
TFUZZ.2021.3079503
" This article is about explainable
artificial intelligence (XAI) for rule-based
fuzzy systems [that can be expressed
generically, as y(x) = f(x)]. It explains
why it is not valid to explain the output
of Mamdani or Takagi-Sugeno-Kang
rule-based fuzzy systems using IF-THEN
rules, and why it is valid to explain the
output of such rule-based fuzzy systems
as an association of the compound antecedents
of a small subset of the original
larger set of rules, using a phrase such as
" these linguistic antecedents are symptomatic
of this output. " Importantly, it
provides a novel multi-step approach to
obtain such a small subset of rules for
three kinds of fuzzy systems, and illustrates
it by means of a very comprehensive
example. It also explains why the
choice for antecedent membership function
shapes may be more critical for
XAI than before XAI, why linguistic
approximation and similarity are essential
for XAI, and, it provides a way to estimate
the quality of the explanations. "
IEEE Transactions on
Evolutionary Computation
Weighted Indicator-Based Evolutionary
Algorithm for Multimodal Multiobjective
Optimizations, by W. Li, T. Zhang,
R. Wang, and H. Ishibuchi, IEEE
Transactions on Evolutionary Computation,
Vol. 25, No. 6, December 2021,
pp. 1064-1078.
Digital Object Identifier: 10.1109/
TEVC.2021.3078441
" Multimodal multiobjective problems
(MMOPs) arise frequently in the real
world, in which multiple Pareto-optimal
solution (PS) sets correspond to the same
point on the Pareto front. Traditional
multiobjective evolutionary algorithms
(MOEAs) show poor performance in
solving MMOPs due to a lack of diversity
maintenance in the decision space.
Thus, recently, many multimodal
MOEAs (MMEAs) have been proposed.
However, for most existing MMEAs, the
convergence performance in the objective
space does not meet expectations. In
addition, many of them cannot always
obtain all equivalent Pareto solution sets.
To address these issues, this study proposes
an MMEA based on a weighted
indicator, termed MMEA-WI. The
algorithm integrates the diversity information
of solutions in the decision
space into an objective space performance
indicator to maintain the diversity
in the decision space and introduces
a convergence archive to ensure a more
effective approximation of the Paretooptimal
front (PF). These strategies can
readily be applied to other indicatorbased
MOEAs. The experimental results
show that MMEA-WI outperforms
some state-of-the-art MMEAs on the
chosen benchmark problems in terms
of the inverted generational distance
(IGD) and IGD in the decision space
(IGDX) metrics. "
IEEE Transactions on Games
The Influence of Social Ties on Performance
in Team-Based Online Games, Y.
Zeng, A. Sapienza, and E. Ferrara,
IEEE Transactions on Games, Vol. 13,
No. 4, December 2021, pp. 358-367.
Digital Object Identifier: 10.1109/
TG.2019.2923223
" Social ties are the invisible glue that
keeps together human ecosystems. Despite
the massive amount of research studying
the role of social ties in communities
(groups, teams, etc.) and society at large,
little attention has been devoted to study
their interplay with other human behavioral
dynamics. Of particular interest is the
influence that social ties have on human
performance in collaborative team-based
settings. Our research aims to elucidate
the influence of social ties on individual
and team performance dynamics. We will
focus on a popular multiplayer online battle
arena (MOBA) collaborative teambased
game, Defense of the Ancients 2
12 IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE | MAY 2022
(Dota 2), a rich data set with millions of
players and matches. Our research reveals
that, when playing with their friends,
individuals are systematically more active
in the game as opposed to taking part in a
team of strangers. However, we find that
increased activity does not homogeneously
lead to an improvement in players' performance.
Despite being beneficial to
low-skill players, playing with friends
negatively affects the performance of
high-skill players. Our findings shed light
on the mixed influence of social ties on
performance and can inform new perspectives
on virtual team management
and behavioral incentives. "
IEEE Transactions on Cognitive
and Developmental Systems
Robot Navigation in Unseen Spaces
Using an Abstract Map, by B. Talbot, F.
Dayoub, P. Corke, and G. Wyeth,
IEEE Transactions on Cognitive and
Developmental Systems, Vol. 13, No. 4,
December 2021, pp. 791-805.
Digital Object Identifier: 10.1109/
TCDS.2020.2993855
" Human navigation in built environments
depends on symbolic spatial information
which has unrealized potential to
enhance robot navigation capabilities.
Information sources, such as labels, signs,
maps, planners, spoken directions, and
navigational gestures communicate a
wealth of spatial information to the navigators
of built environments; a wealth of
information that robots typically ignore.
We present a robot navigation system
that uses the same symbolic spatial information
employed by humans to purposefully
navigate in unseen built environments
with a level of performance comparable
to humans. The navigation system uses a
novel data structure called the abstract
map to imagine malleable spatial models
for unseen spaces from spatial symbols.
Sensorimotor perceptions from a robot
are then employed to provide purposeful
navigation to symbolic goal locations in
the unseen environment. We show how
a dynamic system can be used to create
malleable spatial models for the abstract
map, and provide an open-source
IEEE Computational Intelligence Magazine - May 2022

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