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@@ -111,6 +111,22 @@ <h2>Contributions and Impact</h2>
                 In essence, SatisfIA is pioneering a shift towards safer AI by embedding the principles of aspiration-based decision making at the core of AI agent design. It can be seen as a form of AI that is <a href="https://groups.google.com/g/safe-by-design/about">“safe-by-design”</a>. This research not only challenges conventional maximization paradigms but also opens new avenues for creating AI systems that are not contradicting human values and safety requirements. Not the least, this research poses interesting mathematical and engineering questions!
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             <h2>The Team</h2>
+		<p>
+			Our team currently consists of about a 15 volunteers with various backgrounds, organized into small, 
+			partially overlapping sub-teams of two-to-three persons, working part-time on:
+			<ul>
+				<li>General theory of goal-oriented behavior</li>
+				<li>Theory of information-theoretic safety criteria</li>
+				<li>Design of model-based planning algorithms</li>
+				<li>Design, implementation, and curation of safety-relevant test environments</li>
+				<li>Documentation, educational material</li>
+				<li>Design and implementation of tabular and deep learning algorithms</li>
+				<li>Theory of multi-dimensional aspirations</li>
+				<li>Theory of aspiration-based hierarchical reinforcement learning</li>
+				<li>Theory of aspiration-based behavior in multi-agent environments</li>
+			</ul>
+		</p>
+		<p>Here are some of our team members:</p>
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