-update project acknowledgement

paper/paper.md

@@ -58,7 +58,7 @@ A unique feature of the `ASSUME` toolbox is its integration of **Deep Reinforcem
 Various open-source agent-based models have been developed for studying energy markets, such as PowerACE [@bublitzAgentbasedSimulationGerman2014] and AMIRIS [@schimeczekAMIRISAgentbasedMarket2023].
 Yet, the possible integration of reinforcement learning methods into the behavioral strategies of market agents is currently unique to `ASSUME` and is build upon prior research on multi-agent reinforcement learning [@harderFitPurposeModeling2023].
 Simulations which solely rely on rule-based bidding strategy representation, limit the ability to represent future markets or alternative markets designs, as in reality bidding agents would adapt to the new market design.
-Most notably, `ASSUME` enables the highest number of simultanelously learning market agents in literature [@miskiwExplainableDeepReinforcement2024].  
+Most notably, `ASSUME` enables the highest number of simultanelously learning market agents in literature [@miskiwExplainableDeepReinforcement2024].
 This feature allows for the exploration of new market designs and emergent dynamics in energy markets using a common open-source simulation framework.
 Further unique features of `ASSUME` are the extensive market abstraction which allows to define complex multi-market scenarios as shown in [@maurerMarketAbstractionEnergy2023].
 Even redispatch markets and nodal markets are supported, making it possible to represent network constraints and market coupling.
@@ -91,7 +91,7 @@ For better interoperability with other energy system model data, adapters to int
 
 # Acknowledgements
 
-Kim K. Miskiw, Nick Harder and Manish Khanra thank the German Federal Ministry for Economic Affairs and Climate Action for the funding of the `ASSUME` project under grant number BMWK 03EI1052A.
+This work was conducted as part of the project "ASSUME: Agent-Based Electricity Markets Simulation Toolbox," funded by the German Federal Ministry for Economic Affairs and Energy under grant number BMWK 03EI1052A.
 We express our gratitude to all contributors to ASSUME.
 
-# References
+# References