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jupyter-book/conclusion.md

@@ -17,12 +17,7 @@ LLM struggles to generalize this behavior in a nuanced way beyond a superficial
 depending on whether the role description is altruistic or selfish.
 The unexpected pattern of increased cooperation with defectors and decreased cooperation with cooperators challenges our initial hypotheses and highlights a potential limitation in the LLM’s ability to translate altruism or selfishness into strategies based on conditioned reciprocity. This result suggests that while the agents are sensitive to the general cooperative or competitive nature of the prompts, their capacity to effectively adapt their behavior to their partner’s actions might be more limited.
 
-Another potential limitation of the study is that the LLM has been exposed to
-a vast literature on the iterated Prisoner's Dilemma in its training data,
-and it is unclear how would it perform in more ecologically valid task environments
-that it has no prior exposure to.  This limitation could be addressed by
-inventing new social dilemma games with corresponding task descriptions
-which are not vignettes from the existing literature.
+
 
 Recognizing these limitations, we call upon the research community to further investigate the factors contributing to
 the emergent behavior of LLM-generated agents in social dilemmas, both within and beyond the Prisoner's Dilemma. This
@@ -35,7 +30,13 @@ different contexts, could shed light on the model's adaptability and alignment w
 In future studies, it would be valuable to examine other parameter settings, such as temperature, to explore their
 effects on the emergent behavior of LLM-generated agents. Additionally, as more advanced LLMs like GPT-4 become
 available, it would be interesting to investigate whether they exhibit similar limitations or are capable of more
-nuanced cooperative behaviors in a wider array of social dilemmas. 
+nuanced cooperative behaviors in a wider array of social dilemmas. Another potential limitation of the current study is
+that the LLM has been exposed to
+a vast literature on the iterated Prisoner's Dilemma in its training data,
+and it is unclear how would it perform in more ecologically valid task environments
+that it has no prior exposure to. This limitation could be addressed by
+inventing new social dilemma games with corresponding task descriptions
+which are not vignettes from the existing literature.
 
 By addressing these questions, we hope to
 collectively build a deeper understanding of AI alignment in the context of complex, non-zero-sum interactions across